AI Jobs in Abu Dhabi

We’re Hiring: AI Engineer | UAE NWe are looking for a passionate and hands-on AI Engineer to join our growing team and help build cutting-edge AI-powered solutions.About the RoleAs an AI Engineer, you will be responsible for designing, building, and deploying AI-driven features and applications using large language models (LLMs) such as GPT and Claude. This is a highly practical role focused on developing real-world AI products, not research or model training.What You’ll DoDevelop and deploy AI-powered applications from prototype to productionIntegrate LLMs (GPT, Claude) into business solutions using APIsDesign prompts, workflows, and AI agents to improve output qualityWork with Azure AI Foundry and modern AI platformsContinuously evaluate and adopt new AI tools and technologiesCollaborate with product, design, and engineering teamsWhat We’re Looking ForDegree in Computer Science, AI, or related fieldStrong Python and software engineering skillsExperience working with APIs and LLM integrationsHands-on experience with GPT, Claude, or similar modelsFamiliarity with tools like Git and modern AI frameworksAbility to work in a fast-paced, evolving environmentNice to HaveExperience with LangChain, LlamaIndex, or similar frameworksKnowledge of RAG, vector databases, or Azure AI toolsExposure to open-source LLMs (Hugging Face, Ollama)

AI Data Ops Engineer — Abu Dhabi, UAEWe're hiring an AI Data Ops Engineer for a leading Abu Dhabi-based holding group investing heavily in its data and AI capability. You'll engineer the pipelines that feed everyday AI assistants and enterprise AI products — and you'll be the technical authority reviewing and signing off vendor-delivered data architectures before they reach production. Reports to the AI Solutions Manager. What you'll own:Engineer batch and stream pipelines using Fabric Data Pipelines / Azure Data Factory, Synapse, or Databricks.Implement data quality rules, schema validation, de-duplication, SCD, and reconciliation checks.Operationalize lineage, cataloging, and classifications with Microsoft Purview; enforce RBAC and access patterns.Automate CI/CD via Azure DevOps or GitHub with environment promotion, infrastructure-as-code (Bicep/Terraform), and secrets management via Key Vault.Build feature stores and model-serving data contracts in partnership with MLOps and AI engineering teams.Own reliability: alerts, runbooks, on-call rotation, and cost and performance optimization.Review and finalize vendor-delivered data pipelines and data architecture for AI projects; ensure compliance with client standards for security, performance, and reliability; approve production readiness.Collaborate with delivery partner squads on interface specifications, test data, and delivery checkpoints; support SIT/UAT and production cutover.Define and enforce Data Contracts and SLAs per priority dataset (schema, refresh frequency, quality thresholds, reconciliation checks, and consumer expectations).Own data incident management: classification, RCA, corrective actions, and prevention of recurring nonconformities.Formalize the handshake with AI/ML/DevOps engineers on feature and embedding pipelines, monitoring hooks, and release gates for data-dependent AI deployments. What you bring:6–8 years in data engineering with strong SQL and PySpark and cloud-native data services.Hands-on experience across the Azure data stack: Fabric/Synapse, Data Factory, ADLS Gen2, Delta Lake/Parquet.Bachelor's in Computer Science, Engineering, or equivalent. Core skills and tools required:Python and PySpark, SQL, Lakehouse patterns, medallion architecture.Microsoft Purview: catalog, lineage, classifications; data privacy controls and masking.CI/CD with Azure DevOps or GitHub; IaC with Bicep or Terraform; Docker basics.Observability: Kusto/KQL, Azure Monitor, Log Analytics; performance tuning and FinOps.Production incident response and RCA discipline.Required certifications:DP-700 (Fabric Data Engineer Associate) OR DP-203 (Azure Data Engineer Associate) Desired certifications:Any recognized cloud fundamentals credential (AZ-900, DP-900, AWS Cloud Practitioner, or equivalent)Databricks Certified Data Engineer Associate or Professional  Location: Abu Dhabi, UAEEmployment Type: Permanent, Full-timeExperience: 6-8 yearsSalary Range: 15,000 - 23,000 (AED per month)

IntroductionA career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.Your Role And ResponsibilitiesSupport Data & AI engagements through use-case analysis, agentic AI research, solution documentation, and client deliverable preparation.Eligibility: UAE Nationals are prioritized for this internship.Required Technical And Professional ExpertiseBasic understanding of AI and agentic concepts; analytical and use-case assessment skills; clear written communication.Preferred Technical And Professional Experience Familiarity with Cloud Platforms: Exposure to cloud platforms such as Kubernetes, AWS, Azure, or GCP, and related services is beneficial. Knowledge of Relational and NoSQL Databases: Basic understanding of working with a variety of relational and NoSQL databases, including SQL, Postgres, DB2, and MongoDB. Understanding of Modern UI Frameworks: Interest in modern UI frameworks such as Backbone.js, AngularJS, React.js, Ember.js, Bootstrap, and JQuery is advantageous.

Introduction As part of a cross-functional team of engineers, data scientists, and product owners you will be responsible for designing, implementing, optimizing, and evaluating our product (specific product language here) algorithms. If you love seeing your ideas blossom through their whole life cycle from concept to governing the interaction with millions of users - then Avrioc is the place to be for you! RequirementsMS degree in Statistics, Math, Data Analytics, or a related quantitative field4+ years Professional experience in Advanced Data Science, such as predictive modeling, statistical analysis, machine learning, text mining, geospatial analytics, time series forecasting, optimizationExperience with one or more Advanced Data Science software languages (R, Python, Scala, SAS)Hand on experience with Deep Learning models such as Image classification, Object Detection, Style transfer and similarHands-on experience with any of Python DL libraries such as PyTorch, TensorFlow on kerasHands-on experience with working on CUDA backendHands-on experience with Linux system terminal, shell scriptingWorking knowledge of ELK stack and Message Broker queuesProven ability to deploy machine learning models from the research environment (Jupyter Notebooks) to production via procedural or pipeline approachesComfortable with cloud-based platforms (AWS, Azure, Google)Good planning abilities in order to accurately make project timeline estimates.Ability to show initiative and work independently with minimal direction.Demonstrate a desire to remain current with industry technologies and standards.Self-starter and strong interpersonal skills.Nice to haveComfortable with cloud-based platforms (AWS, Azure).Good communication and presentation skills.Experience with media data (platforms and customer data from either the media agency, technology, or brand side).Good appreciation for the Agile/Scrum methodology

About the RoleWe are seeking a highly skilled and experienced Senior AI Engineer / Technical Lead to join our growing AI & Digital Innovation team. The successful candidate will play a central role in the design and development of enterprise-grade AI solutions, with a focus on building scalable, extensible platforms that support both conversational and transactional AI capabilities across multiple business functions.This is a hands-on technical role suited to an engineer who combines deep AI implementation experience with the ability to lead technically, influence architecture decisions, and collaborate effectively with cross-functional teams. The ideal candidate is passionate about applied AI, has a strong engineering foundation, and has demonstrated experience delivering AI solutions in complex enterprise environments.Key ResponsibilitiesAI Solution Design & DevelopmentDesign, develop, and maintain scalable AI solutions that support both conversational (chat-based) and transactional business functionsContribute to the architecture of AI platforms that are modular and extensible, enabling adoption across multiple business units with varying requirementsEvaluate and recommend appropriate AI tools, models, frameworks, and platforms based on use case requirements and organisational standardsImplement orchestration patterns that coordinate AI agents, models, and workflows in a coherent and reliable mannerAI Integration & EngineeringBuild and maintain integrations between AI components and enterprise systems including CRM, ERP, document management, HR platforms, and communication toolsDesign and implement APIs and integration patterns that enable seamless connectivity between AI capabilities and consuming applicationsImplement Retrieval-Augmented Generation (RAG) pipelines, agentic workflows, and multi-model coordination patterns based on solution requirementsEnsure AI solutions are engineered for performance, reliability, and maintainability in production environmentsConversational & Transactional AIDevelop conversational AI capabilities including intelligent chatbots, virtual assistants, and LLM-powered dialogue systemsBuild transactional AI functions that automate or augment business processes such as document processing, data retrieval, approvals, and workflow automationSupport the design of solutions that handle both real-time and batch AI processing depending on the nature of the business use caseGovernance, Security & Responsible AIApply responsible AI principles throughout the development lifecycle including fairness, transparency, explainability, and data privacyAdhere to and contribute to AI governance practices covering model versioning, monitoring, and auditabilityEnsure AI solutions are built in compliance with organisational security policies, data handling standards, and relevant regulatory requirementsCollaborate with the Information Security team to embed appropriate controls within AI solution designTechnical Leadership & CollaborationServe as a technical lead within the AI team, providing guidance and mentorship to junior engineers and developersWork closely with solution architects, business analysts, and product owners to translate business requirements into sound technical designsParticipate in design reviews, technical discussions, and proof-of-concept evaluationsContribute to the development of internal standards, engineering guidelines, and reusable AI componentsStay current with advancements in the AI space and proactively identify opportunities to apply emerging capabilities within the organisationRequired Qualifications & ExperienceEducationBachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related technical disciplineExperienceMinimum 6–8 years of overall experience in software or AI engineeringMinimum 3–4 years of hands-on experience designing and implementing production AI solutions in an enterprise environmentProven experience working on AI platforms or solutions that span conversational and process automation use casesExperience contributing to or leading the technical delivery of AI integration projects involving multiple enterprise systemsTechnical Skills Area Required ExpertiseAI & ML FrameworksLangChain, Semantic Kernel, AutoGen, LlamaIndex, or equivalent AI orchestration frameworksLarge Language ModelsOpenAI GPT, Azure OpenAI, Anthropic Claude, Gemini, or open-source LLMs (LLaMA, Mistral)Vector DatabasesPinecone, Weaviate, Azure AI Search, pgvector, or equivalentCloud — Azure (Primary)Azure OpenAI Service, Azure AI Studio, Azure Bot Services, Azure API Management, Azure Functions, Azure Logic AppsAzure InfrastructureAzure Kubernetes Service (AKS), Azure Container Apps, Azure Service Bus, Azure Key Vault, Azure MonitorProgramming LanguagesPython (primary), with working proficiency in at least one of JavaScript, C#, or JavaAPI & IntegrationREST API design, event-driven architecture, webhook patterns, API gateway managementRAG & Knowledge RetrievalRetrieval-Augmented Generation (RAG), embedding models, semantic search, knowledge base integrationSecurity & GovernanceAI security controls, data privacy compliance, responsible AI principlesDevOps & MLOpsCI/CD pipelines, containerisation (Docker, Kubernetes), model versioning, prompt management, and monitoringPreferred QualificationsHands-on experience with the Microsoft Azure AI and integration stack, including Azure AI Studio, Azure Integration Services, and Azure API ManagementFamiliarity with agentic AI design patterns and multi-agent coordination frameworksExperience working in regulated industries such as aviation, finance, healthcare, or governmentExposure to enterprise integration platforms such as MuleSoft, Azure Integration Services, or equivalent middlewareMicrosoft Azure certifications such as Azure AI Engineer Associate (AI-102) or Azure Developer Associate (AZ-204) are an advantageFamiliarity with Power Platform (Power Automate, Power Apps) in the context of AI-assisted workflowsKey CompetenciesTechnical Depth — Strong hands-on engineering capability with the ability to move from concept to working solutionProblem Solving — Approaches complex and ambiguous technical challenges in a structured and pragmatic mannerCommunication — Able to explain technical concepts and decisions clearly to both technical peers and non-technical stakeholdersCollaboration — Works well within cross-functional teams and across business units with differing prioritiesInnovation Mindset — Actively follows developments in the AI space and brings relevant ideas and approaches to the teamOwnership — Takes responsibility for the quality and reliability of solutions developed and proactively addresses issuesMentorship — Committed to uplifting team capability through knowledge sharing and hands-on guidance

We are currently looking for a talented Data Scientist –Team Lead & Data Scientist to our team in Abu Dhabi !!!Requirements:Computer vision (object detection, tracking, re-ID, action recognition, segmentation);YOLO, ViT / Transformer models, RF-DETR;VLMs & fine-tuning; • optimisation (TensorRT, ONNX, OpenVINO);Python, PyTorch / TensorFlow;Full MLOps lifecycle; edge-AI constraints (latency, FPS, GPU);Multi-camera tracking;Team leadership, code review & mentoring;Stakeholder communication & solution architecture.CV expertise (detection, tracking, segmentation)Hands-on with YOLO, RF-DETR and similar modelsExperience in fine-tuning Vision-Language Models (VLMs)Quantization ExperienceData preprocessing, augmentation & dataset curationModel training, tuning, evaluation (mAP, precision/recall)Experience with video datasets & annotation feedback loopExperiment tracking (MLflow/W&B)Model optimization basics (TensorRT, ONNX)Understanding of real-world deployment challengesEducational: Computer science or engineering (preferred)3-7 years of hands-on experience in AI/ML applications8-15 years leading and coaching teams, demonstrable track record of projects delivered, bringing value to its recipientsYou are looking for a great opportunity to be part of an amazing challenge. This job is for you!!!About KLANIK:Klanik is an IT consulting company providing solutions to some of the world’s largest industrial and services groups for 10 years.We support our clients with the creation and development of their new products and services around 4 main business lines:➜ Information Technology and Systems (IT & IS)➜ DevOps and Cloud➜ Big Data and AI➜ CybersecurityKlanik is a community of +500 passionate experts empowering clients in 6 countries throughout Europe, Middle East and the Americas.Our Team is dedicated to offer our global clients project support while guaranteeing a consistent level of service alongside a commitment to excellence and strong core values.We’re always looking for smart, talented, driven, down-to-earth, fun-to-work-with people who want to make a positive and meaningful impact!Being a “KLANIK”That means being an out-of-the-box thinker, a precursor who is keen to create, innovate and collaborate in an environment where you can enjoy being yourself and valued for your ideas. It’s being part of a community of experts who have a passion for and stay abreast of the latest technologies.Do you feel like a technology pioneer, full of creative ideas, supported by strong know-how and expertise in the latest technologies? We believe you could be a good fit for our culture!Our culture is our prideAt Klanik, we believe that we are stronger together than we are alone. Trust, ethics, respect, and transparency are deeply fixed in our culture, alongside the pride in a job well done.Our community motto is that people give the best of themselves when they feel listened to, respected, and empowered to develop themselves. Therefore, the better we treat our people, the bigger the success they will achieve. We apply those values on a day-to-day basis among our teams, with our clients, and even with our competitors.Being part of the Klanik community means relying on each other, learning from each other, and growing all together. Our community fosters creativity, innovation, and development within our teams to tackle more and more complex challenges and deliver the best solutions to our clients.

Exciting Opportunity Alert! 🌟 HTC Global Services is hiring AI Engineer for an 1-year extendable contract in Abu Dhabi, UAE (Onsite).HTC Global Services - a leading CMM level 5 global provider of innovative IT and Business Process Services and Solutions since 1990 with headquarters in Troy, Michigan, USA.Key ResponsibilitiesBuild and maintain LLM driven enterprise level applications in real production environment.Design and develop MCP tools using Python, FastAPI, or similar frameworks· Maintain multiple MCP services and LLM integrations.· Develop Angular-based conversational user interfaces with real-time updates.Design scalable architectures capable of supporting high concurrency.Implement monitoring, logging, and tracing for AI workflows.Continuously optimize latency, cost, and response quality.Implement and support multi-agent architectures with context sharing and orchestrationImplement WebSocket-based communication for streaming AI responsesUse Redis for caching, session management, and conversation memoryMaintain scalable services for conversation state, workflow, and memory handling· Strong understanding of API contracts and schema-driven development.Understanding of Prompt engineering, Structured outputs, Tool calling patterns, Model limitations and failure modes.· Good Understanding of Agent orchestration patterns, Role-based agents, Task decomposition, Coordination and fallback mechanisms.Technical SkillsFrontend:Angular / ReactRxJS and reactive programmingReal-time UI updates using WebSocketsBackend:PythonFastAPI / async servicesAPI and middleware developmentAI & Platform:LLM integrations and tool callingMCP / FastMCPLangChain, LangGraphMulti-agent architecturesSystems & Infrastructure:Distributed systems and scalability conceptsWebSockets, event-driven systemsRedis (caching, session, memory)Databases: Cosmos DB, MongoDBVector databases: Pinecone or similarCloud & DevOps:Azure, Azure AI FoundryAzure GitHub (PRs, branching, CI/CD pipelines)Interested candidates please do share your updated CV to mubeenakamal.basha@htcinc.com mentioning your Current CTC, expected CTC and notice period details.#HTCGlobalServices #ITJobs #hiring #lookingforjob #careers #jobs #immediatejoiner #recruitment #technology #jobseekers #interview #lookingforjobchange #newjob #AIEngineer #LLM #RAG #MCP #fastMCP #Python

Job Purpose:The Data Scientist supports the design and implementation of advanced data analytics solutions to enhance AMF’s research, policy analysis, and decision-making capabilities. The role focuses on applying machine learning, AI, and statistical modelling to unlock insights, strengthen data integration, and advance innovation within the organization.Roles and ResponsibilitiesKey AccountabilitiesDesign and implement statistical models, machine learning algorithms, and AI tools for large-scale structured and unstructured dataConduct predictive and prescriptive analytics to support economic and financial policy initiativesContinuously enhance models for performance, accuracy, and scalabilityClean, transform, and manage diverse data sources using automated ETL pipelinesCollaborate with IT to optimize data infrastructure for secure and efficient accessEnsure data quality and alignment with organizational data architecture standardsPartner with research teams on data-driven approaches for frontier topics (e.g., digital economy, AI, climate, financial innovation)Apply advanced techniques such as deep learning and NLP to enhance researchMonitor developments in data science and introduce relevant tools and techniquesDevelop dashboards and visualizations to communicate insights to policymakersCreate data storytelling outputs for publications, policy discussions, and trainingEnsure consistent and accessible data presentation across platforms and reportsComply with data protection regulations, internal policies, and ethical AI standardsSupport implementation of data governance frameworks and quality standardsParticipate in audits and compliance reviews related to data use and accessJob Qualifications and Requirements:Knowledge and Experience:Minimum 5 years of experience in:Data scienceMachine learningAdvanced analyticsPreferably within economic, financial, or public policy sectorsProven ability to develop predictive models and deliver actionable insightsEducation:Bachelor’s degree in:Data scienceComputer scienceStatisticsEconomics Or a related fieldCertifications (Preferred):Recognized certifications such as:Google Data AnalyticsIBM Data ScienceSASCAP (Certified Analytics Professional)

🚀 Hiring: Machine Learning Engineer📍 Location: Abu Dhabi, UAEWe are looking for a talented Machine Learning Engineer to design, build, and deploy scalable machine learning models and AI solutions. This role combines model development, data engineering, and production deployment to deliver innovative, high-impact AI applications.🔹 Key Responsibilities• Model deployment using Docker, Kubernetes• Model optimization (TensorRT, OpenVINO, ONNX, triton, sparsing, pruning)• CI/CD pipelines for ML (Git, Jenkins, GitHub Actions)• Integration with backend & edge devices• Performance tuning (latency, throughput, FPS)• Monitoring model drift & production performance• Strong Python & system design skills• Experience with inference pipelines for video streams🔹Qualifications:Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, AI, or a related field.Additional qualifications, such as certifications or publications in the field of machine learning, are a plus🔹Years of Experience5 to 9 years of experience🔹 Languages:· English. Excellent communication, verbal and written skills.Are you looking for a great opportunity to be part of an amazing challenge with great development possibilities? This job is for you!About KLANIK:Klanik is an IT consulting company providing solutions to some of the world’s largest industrial and services groups for 10 years.We support our clients with the creation and development of their new products and services around 4 main business lines:➜ Information Technology and Systems (IT & IS)➜ DevOps and Cloud➜ Big Data and AI➜ CybersecurityKlanik is a community of +500 passionate experts empowering clients in 6 countries throughout Europe, the Middle East, and the Americas. Our Team is dedicated to offering our global clients project support while guaranteeing a consistent level of service alongside a commitment to excellence and strong core values. We’re always looking for smart, talented, driven, down-to-earth, fun-to-work-with people who want to make a positive and meaningful impact!Being a “KLANIK”That means being an out-of-the-box thinker, a precursor who is keen to create, innovate, and collaborate in an environment where you can enjoy being yourself and be valued for your ideas. It’s being part of a community of experts who have a passion for and stay abreast of the latest technologies.Do you feel like a technology pioneer, full of creative ideas, supported by strong know-how and expertise in the latest technologies? We believe you could be a good fit to our culture!Our culture is our prideAt Klanik, we believe that we are stronger together than we are alone. Trust, ethics, respect, and transparency are deeply fixed in our culture, alongside with the pride in a job well done.Our community motto is that people give the best of them when they feel listened to, respected and empowered to develop themselves. Therefore the better we treat our people, the bigger the success they will achieve. We apply those values on day to day basis among our teams, with our clients and even with our competitors.Being part of the Klanik community means relying on each other’s, learning from each other’s and growing all together. Our community fosters creativity, innovation and development within our teams to tackle more and more complex challenges and deliver the best solutions to our clients.

Job Title: AI Engineer – Azure Databricks | Agentic AI | MCP Servers Experience: 7–12 YearsLocation: Abu Dhabi, UAEJob SummaryWe are looking for an experienced AI Engineer with strong expertise in Azure Databricks, Agentic AI, and Model Context Protocol (MCP) Servers to design and develop next-generation AI solutions for enterprise applications. The ideal candidate will have hands-on experience in building LLM-powered applications, multi-agent systems, and scalable AI data pipelines. Experience in the Revenue Management domain is a strong advantage.Key ResponsibilitiesDesign, develop, and deploy AI solutions using Azure Databricks, Python, and modern AI frameworks.Build and orchestrate Agentic AI applications using multi-agent architectures and autonomous workflows.Develop, integrate, and manage Model Context Protocol (MCP) Servers for secure tool and data access.Design and implement Retrieval-Augmented Generation (RAG) pipelines for enterprise AI applications.Fine-tune, evaluate, and optimize Large Language Models (LLMs) for business use cases.Build scalable data pipelines using PySpark, SQL, and Delta Lake on Azure Databricks.Integrate AI applications with enterprise systems, APIs, and cloud services.Collaborate with data engineers, product teams, and business stakeholders to deliver AI-driven solutions.Monitor AI model performance, ensure governance, security, and responsible AI practices.Stay updated with emerging AI technologies and recommend innovative solutions.Required Skills7–12 years of overall IT experience with strong AI/ML development expertise.Hands-on experience with Azure Databricks, PySpark, Python, and SQL.Strong experience building Agentic AI solutions and multi-agent orchestration.Experience developing and deploying MCP Servers.Expertise in Large Language Models (LLMs), Prompt Engineering, RAG, Vector Databases, and AI orchestration frameworks.Experience with Azure AI Services, Azure OpenAI, or similar cloud AI platforms.Knowledge of REST APIs, microservices, and cloud-native architectures.Strong problem-solving skills and ability to work in Agile environments.About Atain:(http://www.atain.com)Atain is an enterprise orchestration partner that aligns people, processes, and platforms with AI to redefine work and deliver assured outcomes. It is enabled through the SMART Frameworkdriving superior metrics with AI-redefined work, the TechBud platform, a GenAI foundation built on zero-pilot architecture and ISO 42001 standards, a robust partner ecosystem, and deep domain expertise. Atain's Unified Hub continuously senses, predicts, and re-orchestrates work across people, processes, and platforms to deliver assured outcomes. The centers of skill and scale combine deep expertise with AI to deliver assured outcomes. For more information, visit www.atain.comAtain is ISO 27001:2013, CMMI SVC Level 5 and ISAE-3402 compliant for IT, and COPC Certified v6.0, ISO 27001:2013 and PCI DSS 3.2 certified for BPO processes. The organization follows Six Sigma rigor for process improvements.It is our policy to provide equal employment opportunities to all individuals based on job-related qualifications and ability to perform a job, without regard to age, gender, gender identity, sexual orientation, race, color, religion, creed, national origin, disability, genetic information, veteran status, citizenship or marital status, and to maintain a non-discriminatory environment free from intimidation, harassment or bias based upon these grounds.

AI Engineer On-site | Abu Dhabi AppliedAI is a pioneering AI technology company headquartered in Abu Dhabi, committed to innovation and excellence in artificial intelligence solutions in regulated industries such as healthcare, insurance, government, and financial services. Opus is the world's first Knowledge Work AI platform. Built by AppliedAI to pioneer Supervised Automation, a human-in-the-loop model where AI handles repetitive, structured tasks while human experts provide crucial oversight at defined intervals. The platform uses its proprietary Large Work Model to generate and orchestrate outcome-based workflows, enabling a dramatic reduction in the cost of knowledge work and allowing human talent to focus on high-value, creative, and judgement-intensive activities. Role Overview: As an Opus AI Engineer, you will contribute to the development, optimization, and reliability of Opus’s AI infrastructure. You’ll work in a cross-functional UAE-based team to build, maintain, and improve the systems that power Opus’s AI features, from inference pipelines and workflow orchestration to prompt alignment and agentic integrations. Your focus will be on implementing clean, efficient, and observable systems that ensure Opus’s AI features deliver consistent, high-quality performance for users. Key Responsibilities:Develop and maintain AI inference and orchestration pipelines used in production.Optimize model-serving performance, latency, and reliability across live systems.Implement observability, logging, and monitoring for AI components.Contribute to prompt and alignment improvements to enhance response quality and consistency.Refactor existing code for modularity, clarity, and maintainability.Collaborate with senior engineers and product teams to deliver stable, user-facing AI features.Participate in design reviews, testing, and rollout of new systems and improvements.Qualifications:2 - 4 years of experience in ML or backend engineering.1+ years working on LLM prompt design, model behavior shaping, or symbolic product-logic integration into language systems.Strong Python programming skills and understanding of production ML systems.Familiar with orchestration tools (Airflow, Celery, Kubernetes) and cloud environments (AWS, GCP, Azure).Experience deploying and monitoring inference pipelines (e.g. LLMs, CV models, or similar APIs).Knowledge of observability tools and performance debugging.Why join AppliedAI:Opportunity to work with a highly innovative AI technology company.Collaborative and innovative work environment.Growing, entrepreneurial and forward-thinking culture. Career growth and professional development opportunities.Exposure to a thriving ecosystem working from our Abu Dhabi HQ.

The Story So Far: We’re Building a Global Brand in Real EstateHuspy is one of the leading property technology companies in EMEA.Launched in 2020, we now operate in multiple cities across the UAE and Spain, expanding into Saudi Arabia and 3 more European markets by 2026.Today, we own the largest portion of the UAE mortgage market and are one of the fastest-growing players in every European city we’ve entered.We’ve raised over $140 million (Series A and Series B) from the world’s top investors, including Sequoia Capital, Founders Fund and Balderton Capital, to reshape the homebuying journey through powerful technology and agent-first tools.We’ve built a SuperApp that empowers real estate agents and mortgage brokers, bringing cutting‑edge technology to one of the world’s most traditional industries. We’re transforming how property transactions happen — faster, smarter, and better for everyone.We’re not slowing down.The question is: will you be part of what’s next?The Main Event: What You’ll Drive, Build, and OwnReal Estate Market Modeling: Build models applied to challenges such as valuation/pricing leveraging techniques from classic supervised ML to more advanced approaches.Multimodal Embeddings: Create vector representations of Real Estate entities, such as listings, combining images, text, and structured attributes to power search, matching, deduping, or recommendations.Data Analysis & Experimentation: Use SQL/Python to extract, clean, and analyze data; design experiments and evaluate model-product impact with robust metrics.Model Operationalization: Ship models to production with capabilities such as monitoring, automated rollout, or CI/CD (in partnership with engineering).Cross-functional Delivery: Partner with product, engineering, and operations teams to translate business problems into scalable ML solutions.The Perfect Match: What It Takes to Succeed at HuspyProven Experience: 4–8 years in applied data science/ML, delivering models that move real-world KPIs.SQL & Python Mastery: Strong in frameworks such as Pandas/NumPy/Scikit-learn...building reliable data pipelines, model training and evaluation.MLOps Fundamentals: Experience deploying/maintaining models (batch or real-time), versioning, CI/CD basics, observability, and reproducible training.Communication & Ownership: Clear with technical/non-technical stakeholders; can scope, prioritize, and explain tradeoffs.Comfortable with uncertainty, data quality issues, leakage risks, and market dynamics (location, seasonality, inventory shifts).Nice to Have: Software engineering experience; multimodal/vision experience; voice AI (ASR/NLU) exposure.Academic Background: Bachelor’s in STEM (Master’s a plus).By submitting this application, I agree that my personal data will be collected, processed, and retained by the company solely for the purposes of managing and assessing my candidacy.

Headquartered in Abu Dhabi, UAE, specializes in developing AI-driven solutions for defense engineering and supply chain optimization by designing and deploying advanced machine learning models that enhance regulatory compliance, risk prediction, and operational forecasting. The company focuses on integrating generative AI and predictive analytics to automate complex requirements parsing and optimize procurement and logistics efficiencies within security-constrained environments.Job SummaryWe are seeking a Senior Machine Learning Engineer to lead the development and deployment of cutting-edge AI models for our Intelligent Supply Chain and platform initiatives. In this pivotal role, you will oversee the entire lifecycle of machine learning systems—from architectural design and data preprocessing to model training, optimization, and secure production deployment. Your work will bridge generative AI and traditional machine learning, driving innovation in two key areas: the platform, which automates requirements engineering through advanced LLMs, and Intelligent Supply Chain, which delivers predictive risk scoring and demand forecasting. Operating within a structured 'Sprint Zero' to 'Stage Gate' delivery framework, you will ensure that our models are not only highly accurate but also robust, explainable, and deployable within stringent defense-grade security environments. This role demands expertise in both technical execution and cross-functional collaboration, as you will work closely with domain experts, data scientists, and backend engineers to translate complex business challenges into scalable AI solutions. Your contributions will directly impact critical national infrastructure, shaping the resilience of supply chains and the design of defense systems through advanced machine learning applications.Key ResponsibilitiesLead the design and implementation of Large Language Model (LLM) pipelines for automated requirements engineering, focusing on parsing complex regulatory texts such as military standards and building codes to extract structured rules.Convert natural language requirements into executable logic tuples and formalized formats for downstream compliance engines, ensuring seamless integration with technical workflows.Develop Retrieval-Augmented Generation (RAG) architectures to enable semantic search capabilities across technical documentation and historical project data, enhancing query precision and retrieval efficiency.Optimize prompt engineering strategies, including few-shot learning and chain-of-thought techniques, to improve model performance on domain-specific tasks without requiring extensive retraining.Design and deploy time-series forecasting models to predict material demand and spend categories, integrating internal ERP data with external market signals for accurate supply chain planning.Build classification and anomaly detection models to assess supplier risk profiles based on financial health, delivery performance, and geopolitical factors, ensuring robust risk mitigation strategies.Create multi-objective optimization algorithms to balance critical procurement factors such as cost, lead time, and risk, directly supporting data-driven decision-making in supply chain operations.Containerize machine learning models using Docker and Kubernetes, deploying them into secure, on-premise inference environments that meet defense-grade security standards.Construct automated training and inference pipelines using Kubeflow or MLflow to ensure reproducibility, scalability, and seamless integration with existing MLOps workflows.Optimize model inference latency and resource usage through techniques such as quantization and distillation, ensuring efficient performance across available hardware configurations.Implement comprehensive monitoring systems to track model drift and performance degradation in production, establishing feedback loops for continuous improvement and retraining.Required Qualifications5+ years of experience in Machine Learning Engineering, with a proven track record of deploying models into production environments.Expert proficiency in Python and standard ML libraries including PyTorch, TensorFlow, Scikit-learn, Pandas, and NumPy.Strong experience with transformer architectures (BERT, GPT, Llama) and NLP frameworks such as Hugging Face and LangChain.Proficiency with MLOps tools and practices, including containerization (Docker), orchestration (Kubernetes), and experiment tracking (MLflow).Ability to design data preprocessing pipelines for both structured (SQL, tabular) and unstructured (text, PDF) data.Strong grasp of algorithmic principles for implementing custom logic, such as graph traversal or geometric computations.Experience working in agile environments (Sprints) while adhering to rigorous engineering standards and documentation requirements.Ability to quickly learn and apply ML techniques to specialized domains like defense engineering, supply chain, or construction.Strong communication skills to collaborate effectively with Data Scientists, Backend Engineers, and Domain Experts, aligning technical solutions with business needs.Technical SkillsExpert proficiency in Python and standard machine learning libraries including PyTorch, TensorFlow, Scikit-learn, Pandas, and NumPy.Strong experience with transformer architectures such as BERT, GPT, and Llama, and proficiency in NLP frameworks like Hugging Face and LangChain.Deep understanding of MLOps tools and practices, including containerization with Docker, orchestration with Kubernetes, and experiment tracking with MLflow.Ability to design and implement data preprocessing pipelines for both structured data (SQL, tabular formats) and unstructured data (text, PDFs).Experience developing and optimizing retrieval-augmented generation (RAG) architectures for semantic search and knowledge retrieval.Proficiency in prompt engineering techniques, including few-shot learning and chain-of-thought methodologies, to enhance model performance on domain-specific tasks.Strong grasp of algorithmic principles for custom logic implementation, including graph traversal, geometric computations, and multi-objective optimization algorithms.Experience deploying machine learning models into production environments using secure, on-premise inference systems and optimizing inference latency through techniques such as quantization and distillation.Familiarity with time-series forecasting models and their integration with enterprise resource planning (ERP) systems and external market data.Knowledge of classification and anomaly detection models for risk assessment, particularly in domains like financial health, delivery performance, and geopolitical risk scoring.Experience building automated training and inference pipelines to ensure reproducibility, scalability, and compliance with rigorous engineering standards.Ability to implement monitoring systems for tracking model drift and performance degradation in production environments.Location: Abu DhabiLocation: Abu Dhabi, UAEProject Focus: Intelligent Supply Chain & PlatformRole OverviewYou will lead the development and deployment of advanced AI models for the client’s Intelligent Supply Chain and platform initiatives. This role encompasses the full lifecycle of machine learning systems—from architectural design and data preprocessing to model training, optimization, and secure production deployment. Your work will bridge generative AI and traditional machine learning, powering two core initiatives: an automated requirements engineering platform (leveraging LLMs) and an Intelligent Supply Chain system (focusing on predictive risk scoring and demand forecasting). Operating within a structured 'Sprint Zero' to 'Stage Gate' delivery framework, you will ensure models are accurate, robust, explainable, and compliant with defense-grade security standards.LLM & NLP Pipelines (Platform)Design and refine Large Language Model pipelines to parse complex regulatory texts (e.g., military standards, building codes) and extract structured rules. Convert natural language requirements into executable formats (e.g., logic tuples) for downstream compliance engines. Implement Retrieval-Augmented Generation (RAG) architectures to enable semantic search across technical documentation and historical project data. Optimize prompt strategies—such as few-shot learning and chain-of-thought—to enhance model performance on domain-specific tasks without extensive retraining.Predictive & Analytical Models (Supply Chain)Develop time-series forecasting models to predict material demand and spend, integrating ERP data with external market signals. Build classification and anomaly detection models to assess supplier risk profiles based on financial health, delivery performance, and geopolitical factors. Design multi-objective optimization algorithms (e.g., balancing cost, lead time, and risk) to support procurement decision-making.MLOps & ProductionizationContainerize models using Docker and Kubernetes, deploying them into secure on-premise inference environments. Construct automated training and inference pipelines with tools like Kubeflow or MLflow to ensure reproducibility and scalability. Optimize model inference latency and resource usage through techniques like quantization and distillation. Implement monitoring systems to track model drift and performance, establishing feedback loops for continuous improvement.Why Join This Role?This role offers the opportunity to develop cutting-edge intelligence solutions that directly shape and secure critical national infrastructure. Your work will extend beyond theoretical models—your machine learning advancements will actively inform the design of defense systems and strengthen the resilience of global supply chains. If you thrive in applying advanced machine learning to high-impact, real-world challenges within a disciplined engineering framework, this position provides a platform to make a tangible difference. Join a team where innovation meets execution, and your expertise will drive meaningful progress in high-stakes environments.

AI/ML Engineer (Mid, Senior, Lead)Location | Abu Dhabi/Dubai (Hybrid)Comp | $200k-$250k + Equity + PackageFocus | Real-World AI Deployment Across Enterprise & Operational Environments, AI Systems, LLM Applications & Agentic WorkflowsWe’re working with a frontier AI company that builds and deploys AI systems for the world’s most important institutions, automating billion-dollar processes, unlocking national productivity, and modernising the infrastructure of society itself. This is not research for research’s sake. This is applied AI, deployed in the real world.They are backed by some of the world’s most respected founders and AI pioneers, and built a 70+ person team from tier-1 companies. Now, they’re expanding globally and looking for engineers who want to own the deployment of AI that changes how the world works.The RoleAs an AI/ML Engineer, you’ll turn state-of-the-art models into production-grade systems that power national-scale change. You’ll design, deploy, and optimise AI applications that automate some of the hardest real-world processes from energy and healthcare to government operations.You’ll be embedded in small, elite teams that own problems end-to-end: architecture, data, model design, deployment, and iteration. No silos. No bureaucracy. Just impact.What You’ll DoBuild and deploy applied AI systems: from LLMs and agentic reasoning models to scalable data pipelines and production infrastructure.Solve world-scale problems: automate complex workflows, improve public outcomes, and optimise critical national systems.Collaborate with leaders and clients: work directly with government officials, enterprise executives, and industry veterans to translate ideas into deployed solutions.Operate like a founder: own delivery, make decisions fast, and help shape the next generation of applied AI tooling.Stay ahead of the curve: explore the latest GenAI, LLM, and reasoning research to push models from theory to practice.You’ll Thrive Here If You…Have hands-on experience building GenAI or LLM-based applications (agents, RAG, reasoning models).Know your way around Python, PyTorch, JAX, or TensorFlow, with strong software engineering fundamentals.Can work across data pipelines, APIs, and production deployments with speed and precision.Enjoy autonomy, creative problem-solving, and owning solutions end-to-end.Want your work to matter to see it deployed across industries, governments, and communities.Why JoinBuild at frontier scale: ship real systems used by governments, hospitals, and energy leaders worldwide.Elite peers: collaborate with engineers and researchers from tier-1 places.Move fast, own outcomes: you’ll ship code in weeks, not quarters.Meaningful rewards: competitive comp, equity, and ownership tied to real impact.Support to thrive: daily lunches, full benefits, 401(k), and unlimited PTO.If you want to build AI that doesn’t just predict but powers economies, saves lives, and redefines what’s possible , this is where you do it.Join the team building AI that actually ships. Get in touch with danny@salientgroup.com.au for more information.

About the CompanyLiquidity is the world's leading AI-powered private credit firm, pioneering a new standard in growth capital through a nexus of the sharpest minds in private credit and technology. With a global reach and regional expertise in every key market across North America, Europe, APAC and MENA, Liquidity supports visionary growth and mid-market companies in 45+ sectors, deploying multi-billion-dollar capital with unmatched speed, precision and adaptability. Powered by breakthrough decision science technology that deploys growth capital faster than any firm in capital markets history, Liquidity clears the path for innovative companies to move further, faster and at scale. Built on trust, Liquidity is backed by leading financial institutions including MUFG Bank Ltd., Spark Capital and KeyBank.About the RoleWe are looking for a Senior Data Scientist to research, architect, and deploy machine learning models and production-ready AI systems at the heart of Liquidity's credit intelligence platform. You will own the full lifecycle of data science solutions, spanning credit scoring, cash flow forecasting, and autonomous capital allocation workflows, directly shaping how we evaluate creditworthiness and deploy capital across a global portfolio. Beyond modeling, you will translate complex outputs into clear insights and present findings to credit, treasury, and investment stakeholders, closing the loop between algorithmic precision and real business decisions. This role is for highly quantitative problem-solvers who balance innovation with pragmatism, build iteratively from MVPs, and stay genuinely curious about how emerging tools can sharpen their work. You care about reliability, interpretability, and measurable impact, not just model performance in isolation.ResponsibilitiesCredit Intelligence & Predictive Modeling: Build and deploy models for credit scoring, cash flow forecasting, risk classification, and portfolio optimization that directly inform underwriting and lending decisions.Intelligent Workflows: Design data-driven agents with financial guardrails and human-in-the-loop controls for critical treasury and capital allocation decisions.Orchestration & Multi-Agent Systems: Coordinate complex, multi-step workflows using LLM pipelines and orchestration frameworks to analyze market data, liquidity constraints, and portfolio signals.Data Storytelling & Dashboarding: Translate model outputs and portfolio insights into clear, actionable dashboards and reports for credit and executive stakeholders.MLOps & Model Lifecycle: Manage the full model lifecycle, including experiment tracking, versioning, deployment, and monitoring, to detect drift, ensure reproducibility, and maintain production reliability.Production Engineering: Develop model-serving APIs and deploy within event-driven cloud architectures, collaborating with engineering on scalable, well-observed systems. Qualifications6+ years of experience in Data Science, Quantitative Modeling, or AI/ML, including 2–4 years deploying production-grade ML models, agentic AI, or LLM pipelines.Modeling: Time-series forecasting, credit scoring, regression, classification, and optimization; proficiency with tree-based models (XGBoost, LightGBM) and model interpretability techniques such as SHAP.Technical Stack: Advanced Python (Pandas, Scikit-learn); MLOps tooling (MLflow); exposure to deep learning frameworks (PyTorch or TensorFlow) a plus.Data & Databases: Strong SQL; experience with Postgres, MySQL, or Databricks.Visualization: Fluency in at least one dashboarding tool (Streamlit, Tableau, or Power BI).AI Fluency: Stays current with the rapidly evolving AI landscape; able to translate business problems into clear AI directives and effectively supervise and evaluate intelligent workflows.Software Engineering: Strong coding practices, with the ability to write clean, maintainable Python and debug complex issues across data pipelines, model serving, and integrated systems.Communication & Presentation: Able to distill complex quantitative work into clear narratives and present findings confidently to credit, investment, and executive stakeholders. Preferred SkillsMaster's degree or Ph.D. in a quantitative field (Computer Science, Statistics, Mathematics, Finance, etc.).Domain experience in FinTech, private credit, or quantitative finance.Infrastructure & deployment: Docker, CI/CD pipelines, cloud platforms (AWS Lambda, Serverless, Containers), and observability tooling (Langfuse, CloudWatch, or Datadog).NoSQL and alternative data stores: MongoDB, Neo4j, and vector databases.Familiarity with web technologies (REST APIs, basic HTML/JS) and ETL pipeline design.Experience with FastMCP or MCP-based tooling. Pay range and compensation package[Pay range or salary or compensation]Equal Opportunity Statement[Include a statement on commitment to diversity and inclusivity.]

Vatic is looking for an AI engineer in Abu Dhabi with proven experience with large foundational models. Our environment is highly collaborative, fostering innovation and growth. We are interested in a variety of data modalities (language, vision, multimodal, and structured data) and modern model architectures. We are looking for team players who are interested in developing next-generation platforms and tools for Machine Learning as well as conducting state-of-the-art research.As an AI Engineer you will:Play a crucial role in designing and developing cutting-edge frameworks that can serve as the future tools to help develop innovative platforms and systems that drive our trading and research efforts, with a different lens through foundational models. Work closely with a team of passionate researchers and engineers to make sure such frameworks are compatible with recent cloud platforms, popular ML frameworks and libraries, as well as modern model architectures.play a central role in defining and running large-scale experiments that contribute towards rigorous evaluation and in-depth model analysis.We employ a team of talented engineers who have been recognized as leaders in our field. We are passionate about hiring the best and brightest, empowering them with the tools and freedom they need to be successful.If you possess the following, we would love to explore what is available for you with our team:Keen interest in training, evaluation, understanding, and innovation of foundational modelsAdvanced proficiency with Python development in a Linux environmentStrong understanding of machine learning, deep learning, and generative AI methods and technologiesDirect experience with multi-GPU model trainingDemonstrable success building high performance softwarePerformance tuning/optimization of software and algorithmsFamiliarity with parallel computing models and frameworksStrong analytical and problem-solving skillsA passion for trading, research, and technologyExcitement and interest in using readily available open source technologies and prototypesExcellent communication skillsConfident team player motivated by a fast-paced environmentAt Vatic, we're serious about our work—but we also believe in balance, growth, and having fun along the way. Here's what you can expect:Flat structure with direct executive exposure – Work closely with leadership and make an impact from day one.Comprehensive health benefits – Full health insurance coverage for employees and dependents.Daily meals provided – Enjoy free lunch at the office.

Applied AI - Forward Deployed EngineerLocation: Abu Dhabi, UAE (relocation fully supported)About the opportunityWe're partnered with a leading AI company in Abu Dhabi building agentic AI products for major enterprise and government clients.This is a forward-deployed role at the heart of their flagship agentic AI product. You'll sit at the bridge between the product and the client: taking ambiguous, high-value business problems and turning them into working AI systems that run in production. You'll build the solution and help shape what gets built.What you'll doWork directly with major clients to translate ambiguous business problems into well-framed agentic workflows, with clear success criteriaOwn the design, build, and deployment of LLM-powered agents end-to-end, from early prototype to production-grade systemFlex into whatever the problem demands, backend, frontend, data, integration, to ship the most effective solutionBuild features for the core agentic platform across the full product lifecycleAct as the trusted technical voice in the room with senior client stakeholders, then go and build what you've scopedWhat we're looking forThis is a hybrid profile, the rare engineer who combines the following key elements:Technical depth, you build production-grade software in Python; you've shipped RAG and agentic applications (multi-step reasoning, tool use, patterns like ReAct or Plan-and-Execute); you know the modern LLM stackProduct instinct, you think in terms of what to build and why, not just how; you're comfortable owning a use case end-to-endClient-facing strategic ability, you can lead a technical conversation with senior stakeholders, navigate ambiguity, and translate business needs into technical realityLanguages: Arabic and French speakers are particularly well placed given the client and team environmentPlus:3-6 years' experience with a strong software engineering or data science foundationA bias to build, comfort with ambiguity, and a product-driven (not consulting-style) mindsetBackground we love (not required, but a strong signal):Dual-track engineering + strategy backgrounds, applied-AI consulting with real technical depth, frontier-lab engineering, founder experience, or an engineering + business education.How the team worksWhat matters is what you ship, not the hours you spendLow ego, high standards. The best idea wins, whoever it comes fromDirect, timely feedback because people care about the workMinimal bureaucracy, you talk to whoever you need to talk toThe packageCompetitive, tax-free salaryFull relocation support to Abu Dhabi is providedThe chance to build agentic AI that goes live at serious scaleInterested?Send your CV or DM me directly for a confidential conversation.

We’re looking for someone who will play a pivotal role in leading the development and adoption of high impact data science and machine learning projects, that drive measurable business outcomes across a variety of different banking domains. This is a rare opportunity to work closely with business and technology stakeholders to ensure insights and models are effectively embedded into decision making processes.What we’re looking for:Strong expertise in designing, developing and deploying data science and machine learning modules to improve decision makingProven experience with utilizing time-series modelling techniques to solve complex business problems using structured and un-structured dataAdvanced Python and ML developmentConfident in monitoring and managing resistance by identifying potential barriers early, addressing stakeholder concerns proactively, and ensuring alignment with transformation objectives.Academic background in a relevant STEM discipline (MSc preferred, ideally in Mathematics, Data Science, AI, Machine learning, or similar)Why this opportunity stands out:Work within a leading bank within the Middle east.Collaborate with a high-calibre, international team in a forward-thinking environmentEnjoy a highly competitive, tax-free package, including:Attractive monthly salaryFull international medical coverageVisa sponsorshipRelocation support (if applicable)

Urgent requirement for AI/ML Specialist expertise in Gen & Agentic AI in banking domain(preferred) required for our banking clients in Abu Dhabi ,UAEImplement cloud-based AI solutions leveraging GPT, Claude, and other LLMs--MustAI/ML Specialist with deep expertise in Generative & Agentic AI, advanced deep learning, and strong proficiency in cloud-based LLMs--MustExperience with open-source models and frameworks & ONNX for model interoperability--Must Deep learning backround(Both NLP and Computer Vision) ,Vector DB Experience(Azure Document DB, Elasticsearch, Faiss etc.)--MustDeep understanding of embedding model & Hands-on Vector DB experience (Azure Document DB, Elasticsearch, Faiss)--Must- Role SummaryWe are seeking a highly skilled AI/ML Specialist with deep expertise in Generative & Agentic AI, advanced deep learning, and strong proficiency in cloud-based LLMs. The ideal candidate will drive innovation in embedding models, prompt engineering, and scalable data processing pipelines, contributing to cutting-edge AI solutions across NLP and Computer Vision domains.Key ResponsibilitiesDesign, develop, and deploy AI/ML models for production environmentsImplement cloud-based AI solutions leveraging GPT, Claude, and other LLMsArchitect and optimize vector databases (Azure Document DB, Elasticsearch, Faiss)Advance research in embedding models and prompting techniquesConduct rigorous model evaluation and benchmarkingCollaborate with cross-functional teams to integrate AI into products and platformsMaintain robust data pipelines and ensure efficient data processing workflowsContribute to research initiatives and knowledge sharing within the AI communityQualificationsMSc or PhD in Computer Science, AI/ML, or related field (preferred)Proven expertise in TensorFlow and PyTorchStrong command of Python programmingDeep knowledge of SQL & NoSQL databasesExperience with open-source models and frameworksFamiliarity with ONNX for model interoperabilityDemonstrated success in model evaluation and performance optimizationHands-on experience with vector DBs and scalable retrieval systemsSkills: genai,ml,ai

DeepLight AI is a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking. Our team combines deep expertise in data science, statistical modeling, AI/ML technologies, workflow automation, and systems integration with a practical understanding of complex business operations.The Artificial Intelligence (AI) Engineer is a specialist role focused on the engineering, deployment, and scaling of advanced AI systems to drive the Bank's digital and operational transformation. This position is responsible for building the robust technical foundations required for enterprise-grade applications, including Conversational AI agents, operations automation, and Generative AI initiatives. By developing high-performance pipelines and reusable components, you will ensure that AI products are reliable, compliant, and capable of delivering next-generation experiences for both customers and employees.As the AI Engineer with Deeplight, your responsibilities will include:Building and scaling next-generation Conversational AI platforms (voice and chat) using LLM-based agents and multi-agent orchestration frameworksDeveloping automation agents for critical banking functions such as KYC, compliance, risk monitoring, and customer serviceImplementing Retrieval-Augmented Generation (RAG) pipelines utilizing vector databases and knowledge graphs to power enterprise searchModel Optimization: Design and refine prompts to optimize LLM performance and apply advanced parameter-efficient fine-tuning techniquesOperationalizing embedding models and custom ML solutions by building APIs, SDKs, and CI/CD pipelines with automated retraining and drift managementEstablishing engineering standards for model fairness, security, explainability, and disaster recovery to ensure operational resilienceActing as an analytics translator, identifying opportunities for leveraging data to solve complex business problems across functional teamsAs an AI consultancy, our greatest asset is the expertise of our people.While technical mastery is the foundation of what we do, the ability to bridge the gap between complex data science and actionable business value is what defines your success with Deeplight.We're looking for individuals who are not only world-class in their fields of specialism, but also compelling communicators and persuasive advocates for their own skills.You will be the face of our firm, tasked with building trust, articulating the "why" behind your technical decisions, and effectively "selling" your vision to high-level stakeholders.If you thrive on the challenge of presenting cutting-edge solutions as much as you do on building them, you will fit right in.RequirementsWhat we need from you:Bachelor's degree in a quantitative field (Computer Science, AI, Software Engineering, or Mathematics); a Master's degree in AI/ML is highly preferred5+ years in AI/ML engineering or large-scale digital product engineering, ideally within a major digital transformation or digital-only bank projectProven experience deploying large-scale AI/ML solutions within a regulated environment (Banking or Financial Services preferred)Hands-on experience with MLOps tools (MLflow, CI/CD) and data visualization platforms (Tableau, Power BI)Expert-level programming in Python specifically for ML/AI engineering and Generative AI applicationsDeep knowledge of transformer models, multimodal architectures, and agentic AI systems (multi-agent frameworks/human-in-the-loop)Expertise in vector databases (Pinecone, Weaviate, Milvus), knowledge graphs, and both SQL/NoSQL systems (Postgres, MongoDB)Proficiency in Azure AI Foundry or AWS SageMaker, including serverless deployments (Lambda/Azure Functions) and containerization (Docker, Kubernetes)Deep understanding of LLM evaluation metrics and observability frameworks for monitoring agentic workflowsIt would also be beneficial if you have experience of the following:Ability to quickly build and test AI prototypes while maintaining a focus on enterprise-grade security and complianceActive engagement in the AI community with a track record of evaluating emerging tools like LangChain, CrewAI, and BedrockExceptional communication skills to bridge the gap between technical requirements and business objectives for non-technical stakeholdersDeep understanding of emerging trends such as Reinforcement Learning from Human Feedback (RLHF) and multimodal AIBenefitsBenefits & Growth Opportunities:Competitive salaryVisa Sponsorship for the successful individual. Comprehensive health insurance for the successful individual. Professional development and certification supportOpportunity to work on cutting-edge AI projectsCareer advancement opportunities in a rapidly growing AI companyThis position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients.At DeepLight AI, we recognise that diversity drives innovation. We are committed to fostering an inclusive environment where individuals with different thinking styles can thrive and contribute their unique strengths to our specialised AI and data solutions.Our goal is to ensure our application and interview process is accessible, predictable, and fair for all candidates.If you require any specific adjustments to the application process, or if you require any reasonable adjustments should you be successful in being processed to the interview stage, please do let us know. This information will be kept strictly confidential and will not impact hiring decisions.

Hi All,We are seeking a highly skilled Data Scientist with strong expertise in Machine Learning, Generative AI, and Large Language Models (LLMs) to design, develop, and deploy advanced AI-driven solutions. The ideal candidate should have hands-on experience in building scalable ML models and GenAI applications for enterprise use cases.Key ResponsibilitiesDesign, build, and deploy machine learning models for business problemsDevelop and implement Generative AI solutions using LLMs (e.g., GPT, LLaMA, etc.)Build and optimize RAG (Retrieval-Augmented Generation) pipelinesWork on prompt engineering, fine-tuning, and model optimizationDevelop AI agents and automation workflows using frameworks like LangChain / LangGraphPerform data preprocessing, feature engineering, and model evaluationCollaborate with cross-functional teams to translate business needs into AI solutionsDeploy models into production using cloud platforms and APIsMonitor, evaluate, and improve model performanceKey Skills Required✅ Core SkillsStrong knowledge of Machine Learning & Deep LearningExpertise in Python (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow)Hands-on experience with LLMs and Generative AI✅ GenAI & LLM SkillsExperience with OpenAI, Hugging Face, or similar ecosystemsStrong understanding of RAG architectures, embeddings, vector databasesExperience in prompt engineering and LLM fine-tuningExposure to Agentic AI frameworks (LangChain, LangGraph)✅ Data & EngineeringExperience with SQL, ETL pipelines, and data processingKnowledge of Databricks / Spark (preferred)Familiarity with vector databases (FAISS, Pinecone, ChromaDB)✅ Cloud & DeploymentExperience with Azure / AWS / GCPKnowledge of ML deployment (APIs, Docker, CI/CD)Only Immediate joiner shares their profiles on priya.singh@atain.com

AI EngineerLocation: Abu Dhabi, UAE | Type: Permanent, Full-TimeWe recently had a brand new and exciting opportunity for an AI Engineer to join a telecommunications Defence Tech company based in Abu Dhabi. The AI Engineer will be designing and implementing production grade AI models to integrate with Oracle EBS.If you are a AI Engineer who has a strong software engineer background using Python, AI (LLMs & RAG) alongside on-prem ERP integration experience then this would be the perfect next step for you.Requirements for the AI Engineer:Experience designing and implementing AI models (LLMs, RAG & Predictive Analytics)Expertise in creating and maintaining APIs using PythonMust have on-prem ERP experience, preference is Oracle EBSMust be based in the UAE already or keen to relocateSalary - 25k-28k AED per month + UAE comprehensive benefits.Apply now to be considered for this great opportunity!

Lead AI EngineerTelco & MediaAbu Dhabi, United Arab EmiratesPermanent roleThis role requires you to work onsite in Abu Dhabi. We are looking for a Lead AI Engineer for a media company in Abu Dhabi. You will have an opportunity to work in business with complete buy-in from C-Level stakeholders to become AI-first.Experience needed:8+ years in industry (AI/Engineering)Own delivery of enterprise AI deliverablesDevelop AI InfrastructureBuild and deploy AI agents and internal toolsEvaluate and integrate emerging AI models, APIs, and infrastructure componentsIdentify patterns where AI can enhance work across business and for customersExperience with the latest LLM's, RAG and Agentic AIExperience with vector DB'sLead MLOPs processesTrack developments in AI and translate relevant advances to implementEducationPhD or MSc in AI, DS, Engineering or other relevant STEMPackageTax free salaryVisaMedicalFlightsBonusRelocation allowances (cash, hotel, flights)If you feel you have the right skills, please apply and share your CV, so we can arrange a confidential discussion.**Due to the high volume of applicants, only relevant candidates will be contacted**

The Data Science Expert leads and develops high-performing teams of data scientists and data engineers to deliver advanced analytics, AI, and predictive modeling solutions for ENEC’s nuclear operations. This role ensures technical excellence, compliance with nuclear safety standards, and the delivery of actionable insights that optimize plant performance, fuel cycle management, and operational reliability. The Expert acts as a strategic advisor, technical authority, and mentor, driving innovation and embedding analytics into the core of ENEC’s mission.Responsibilities• Strategic Leadership:Drive the data science and analytics strategy for nuclear operations, ensuring alignment with ENEC’s safety, reliability, and business objectives.• Technical Excellence:Oversee the design, development, and deployment of advanced models for reactor performance, fuel cycle optimization, outage prediction, and anomaly detection.• Team Leadership:Lead, mentor, and develop multidisciplinary teams of data scientists and engineers, fostering a culture of innovation, collaboration, and continuous improvement.• Stakeholder Engagement:Collaborate with plant, fuel, engineering, and regulatory teams to embed analytics into operational workflows and decision-making.• Governance & Compliance:Ensure all analytics activities adhere to nuclear safety culture, regulatory requirements, and robust data governance.• Operational Excellence:Monitor and improve the impact of analytics on plant reliability, fuel efficiency, and business outcomes.• Expert Knowledge Application:Apply advanced expertise in statistical modeling, machine learning, and AI to develop solutions for complex nuclear analytics challenges, ensuring technical rigor and industry compliance.• Complex Problem Solving:Lead the resolution of ambiguous and high-impact analytics issues by designing innovative approaches, conducting root cause analysis, and implementing corrective/preventive actions to enhance operational reliability.• Professional Know-How:Utilize deep technical know-how to architect, validate, and deploy digital twins, predictive maintenance models, and fuel cycle optimization tools, ensuring best practices in MLOps and automation.Responsibilities and Accountabilities:• Define, communicate, and continuously refine the analytics vision and multi-year roadmap for nuclear operations.• Advise executive leadership on leveraging AI and advanced analytics for plant optimization, fuel cycle management, and operational excellence.• Lead the development of business cases for analytics investments focused on nuclear plant performance, predictive maintenance, and fuel efficiency.• Align analytics initiatives with ENEC’s digital transformation, safety culture, and national mission.• Monitor industry trends and emerging technologies to ensure ENEC remains at the forefront of nuclear analytics.Responsibilities and Accountabilities:• Direct the design, development, and deployment of advanced statistical, machine learning, and AI models for nuclear plant operations, fuel cycle analysis, and safety-critical predictions.• Oversee the development and validation of digital twins, predictive maintenance models, and fuel consumption forecasting tools.• Ensure all models are validated against nuclear industry standards, regulatory requirements, and plant-specific constraints.• Lead the adoption of MLOps best practices for continuous monitoring, retraining, and governance of models deployed in nuclear environments.• Drive the adoption of automation, CI/CD pipelines, and advanced monitoring for analytics operations.• Lead technical reviews, audits, and assurance activities to maintain high standards of quality, reliability, and compliance.• Ensure robust documentation, explain ability, and auditability of all models and analytics solutionsCertification - Relevant certifications in AI/ML, MLOps, and Data Governance.Education and Experience - Min - Master’s degree in data science, computer science, engineering, or related discipline. Proven experience leading data science teams in regulated environmentsPref - PhD or equivalent. Experience in nuclear, energy, or highly regulated sectors.8 years of relevant experience

Data ScientistLocation: Abu Dhabi, UAE Full-timeExp.: 7-8+ Yrs.Key Skills: Generative AI, Regression, Modeling, LLM(Revenue management exp. is preferred)Role OverviewWe are seeking a highly skilled Data Scientist with strong expertise in Machine Learning and AI, along with experience in the airline or aviation domain. The ideal candidate will drive data-driven innovation, build scalable AI solutions, and enhance customer and operational experiences within the travel ecosystem.Key ResponsibilitiesDesign, develop, and deploy Machine Learning and AI models to solve business problems in the airline domain (e.g., pricing, demand forecasting, customer experience, operations).Build and implement advanced analytics solutions using NLP, deep learning, and Generative AI techniques.Develop AI-powered applications such as chatbots, recommendation systems, and intelligent automation tools.Work with large-scale structured and unstructured datasets to extract actionable insights.Collaborate with cross-functional teams including business, engineering, and product teams to deliver impactful solutions.Deploy scalable solutions using cloud platforms (AWS/GCP/Azure) and modern frameworks.Monitor model performance and continuously improve accuracy and efficiency.Required Skills & QualificationsStrong experience in Machine Learning, Deep Learning, and AI techniques.Hands-on experience with NLP, LLMs, and/or Generative AI (RAG, chatbots, etc.).Proficiency in Python, SQL, and data processing tools (e.g., PySpark).Experience with cloud platforms such as AWS, GCP, or Azure.Knowledge of model deployment frameworks (FastAPI, Flask, Docker).Experience working in the airline/travel domain (pricing, operations, customer analytics, etc.) is highly preferred.Strong problem-solving skills and ability to translate business problems into analytical solutions.Preferred QualificationsExperience with real-time data processing and AI-driven automation.Familiarity with tools like LangChain, Snowflake, or similar modern data platforms.Prior experience working in global or cross-functional teams.It is our policy to provide equal employment opportunities to all individuals based on job-related qualifications and ability to perform a job, without regard to age, gender, gender identity, sexual orientation, race, color, religion, creed, national origin, disability, genetic information, veteran status, citizenship or marital status, and to maintain a non-discriminatory environment free from intimidation, harassment or bias based upon these grounds.

Company OverviewOpen Innovation AI is a global technology company that specializes in developing advanced solutions for managing AI workloads. Its flagship product, the Open Innovation Cluster Manager (OICM), orchestrates complex AI tasks efficiently across diverse infrastructures. The platform is hardware-agnostic, optimized for various GPUs and accelerators hardware, and facilitates seamless integration and scalability for enterprise AI applications. Open Innovation AI focuses on optimizing and simplifying AI workload management and making AI technologies accessible to organizations of all sizes. With its innovative solutions, companies can reduce operational costs, accelerate time to value, and maximize their return on investment, ensuring that their AI strategies contribute directly to enhanced business outcomes.Role Overview:We're hiring an AI Engineer to build the applied AI that our agentic platform runs on. The job is to take what's actually working in LLMs and agent systems right now and turn it into features people can depend on. Some of it is straight engineering. Some of it is keeping up with a field that moves every week reading the new work, trying it, and shipping the parts that hold up.Role Responsibilities:Write clean, reliable code for the agentic and applied-AI features at the core of the product.Get LLM capabilities into production: agents, orchestration flows, RAG, tool use, multi-agent setups.Try new models, techniques, and frameworks. Prototype them, see if they hold up, bring the good ones in.Build the evals, benchmarks, and observability we need to actually know whether an agent is getting better or worse.Keep AI workloads running in production automation, scaling, the unglamorous parts.Work with product and other teams to turn what users need into specs you can build against.Debug, test, and tune the core product when it's slow or wrong.Review code and help junior engineers level up.Keep an eye on what's new and flag what's worth the team's attention.Required experience & QualificationA degree in CS or engineering, or the equivalent experience we care more about what you've builtStrong Python or TypeScript. Either is fine.You've built applied AI or ML and shipped it to real users, not just in notebooks.Hands-on with LLMs and the current toolset: orchestration frameworks, agentic patterns, RAG, prompt engineering, fine-tuning, evals a solid subset of these.Some exposure to MLOps/LLMOps: deploying, scaling, and monitoring models in production.Real grounding in software design. You should be able to reason about architecture, not just wire up API callsComfortable with Git.You can make progress on a deadline and explain your thinking to the people around youNice to have:A strongly typed language like Go, Java, or C++.Open-source contributions, papers, or applied research.The habit of reading AI research and actually turning it into product changes.

Job Purpose As a Data Scientist, you will apply machine learning and deep learning techniques to solve real-world business problems across numeric and text-based analytics. You will work across the full data science lifecycle—from data acquisition and feature engineering to model development and deployment—collaborating closely with engineering, product, and DevOps teams to deliver customer-centric AI solutions.Job DescriptionKey ResponsibilitiesDevelop and deliver high-quality machine learning and deep learning models across a broad range of analytics use cases.Understand the practical scope and constraints of AI models within products and apply appropriate modeling techniques to ensure business relevance and technical robustness.Acquire data from diverse sources, performing data exploration and preprocessing on structured and unstructured datasets, conducting feature engineering, evaluating algorithms and architectures, and iteratively refining models to improve performance.Identify valuable data sources and automate data collection and preparation processes where possible.Build, fine-tune, and maintain machine learning pipelines, integrate algorithms and packages into the platform, and contribute new models to the platform marketplace.Collaborate closely with engineering and DevOps teams to support model deployment and operationalization.Contribute to applied research activities, propose data-driven solutions to business challenges, and work with product, support, and client-facing teams to ensure successful rollout of AI solutions into trials and general availability.Key SkillsStrong foundation in the theory and applied practice of machine learning and deep learning. Experience developing pipelines for structured and unstructured data.Hands-on experience with deep learning frameworks such as TensorFlow and PyTorch, and machine learning libraries such as scikit-learn.Proficiency in Python, with working knowledge of Java or R.Experience developing and exposing models through RESTful APIs and containerized deployments using Docker.Strong coding practices, including appropriate use of data structures and clean, maintainable code.Applied experience in NLP, including the use of transformer-based models and libraries such as Hugging Face, spaCy, or Gensim. Familiarity with SQL, Pandas, Apache Spark, and data processing at scale.Experience using ML lifecycle tools such as MLflow.Strong analytical thinking, communication skills, and the ability to present technical concepts clearly to internal and external stakeholders.Ability to work collaboratively across multidisciplinary teams.Qualifications and ExperiencePreferred Educational Qualifications and Professional CertificationsBachelor’s degree in Artificial Intelligence, Data Science, Business Analytics, Computer Science, Mathematics, Engineering, or a related field is preferred. Relevant professional certifications are an advantage.ExperienceMinimum 4–6 years of professional experience in data science or applied machine learning roles.Desirable SkillsExperience working with large language models (LLMs), including offline deployment scenarios. Exposure to cloud-based environments (AWS, GCP, Azure). Experience with data visualization tools and collaborative environments such as Jupyter Notebooks and Git-based workflows. Domain experience with education or finance datasets is an advantage.

The Center for Interdisciplinary Data Science and Artificial Intelligence (CIDSAI) at NYU Abu Dhabi seeks to recruit a Research Engineer to support the design and implementation of interactive AI and data science platforms across the Center’s research clusters.The successful candidate will collaborate with researchers and faculty across domains such as Foundations of Data Science, Enabling Technologies, Health, Education and Personalized Learning, and Bias, Ethics & Privacy, contributing to the development of prototypes, interfaces, and software infrastructure that translate research outputs into usable tools.Key ResponsibilitiesDesign, develop, and maintain web-based and AI-powered platforms supporting CIDSAI research projects.Collaborate with faculty and postdocs on projects such as: Mathematical Collaboration Platform, Personalized Learning Systems and SmartClass AI Tutors, Health-focused conversational AI and multimodal interfaces, Bias detection and fairness-aware tools for ethical AI.Integrate machine learning models, visualization dashboards, and backend services.Contribute to data collection, testing, documentation, and dissemination of open-source resources.QualificationsBachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.Strong programming skills.Experience with machine learning frameworks and backend systems.Familiarity with cloud computing, API integration, data visualization, and database management.Ability to work in interdisciplinary research environments bridging theory, applications, and ethics.The appointment is for two years, with the possibility of renewal. The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be accepted immediately and candidates will be considered until the position is filled. To be considered, all applicants must submit a cover letter, curriculum vitae, transcript of degree, a maximum three pages summary of research accomplishments and interests, and at least 2 letters of recommendation, all in PDF format.Further questions may be directed to Professor Pierre Youssef at yp27@nyu.edu.About NYU Abu Dhabihttps://nyuad.nyu.edu/en/NYU Abu Dhabi is the first comprehensive liberal arts and research campus in the Middle East to be operated abroad by a major American research university. Times Higher Education ranks NYU among the top 30 universities in the world, making NYU Abu Dhabi the highest-ranked university in the UAE and MENA region. NYU Abu Dhabi has integrated a highly selective undergraduate curriculum across the disciplines with a world center for advanced research and scholarship. The university enables its students in the sciences, engineering, social sciences, humanities, and arts to succeed in an increasingly interdependent world and advance cooperation and progress on humanity’s shared challenges. NYU Abu Dhabi’s high-achieving students have come from over 120 countries and speak over 100 languages. Together, NYU's campuses in New York, Abu Dhabi, and Shanghai form the backbone of a unique global university, giving faculty and students opportunities to experience varied learning environments and immersion in other cultures at one or more of the numerous study-abroad sites NYU maintains on six continents.NYUAD is committed to upholding a culture of non-discrimination, anti-harassment, dignity, and mutual respect; providing equal access and opportunity; and fostering academic excellence in learning, research, and teaching.UAE Nationals are encouraged to apply.Equal Employment Opportunity StatementFor people in the EU, click here for information on your privacy rights under GDPR: www.nyu.edu/it/gdprNYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply for vacant positions at all levels.Sustainability Statement NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu/sustainability

The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health records and medical images, for applications pertaining to patient diagnostics and prognostics.SkillsWe are seeking a Research Assistant to join the team and make significant contributions to the field. The researcher is expected to have (i) strong machine learning skills to improve model performance and robustness, and (ii) exemplary passion and motivation to pursue multidisciplinary research at the intersection of computing and healthcare. Methodologies of interest include:multi-modal learning,foundation models, including large language models,agentic AI,multi-agent AI systems,transfer learning,self-supervised learning,and federated learning.The Research Assistant will be primarily based at NYU Abu Dhabi. The researcher will report directly to Dr. Farah Shamout and work in close collaboration with other researchers, PhD students, and undergraduate research assistants. The researcher will engage with our regular collaborators across the NYU campuses and local medical institutions in the UAE.Key ResponsibilitiesResearchSupport the supervisor in developing and implementing the research agenda;Conduct high-quality and innovative research primarily focused on ML for healthcare;Design and implement experiments to compare proposed work with SOTA baselines;Publish research findings in high-impact journals and conferences;Communicate and present research findings at international academic gatherings;Create, maintain, and document high-quality research code for reproducibility;Maintain good practice in managing and accessing sensitive medical datasets;And collaborate with scientists within the NYU Global Network and in Abu Dhabi.Minimum QualificationsCurrently has or is in the process of completing a bachelor’s or master’s degree from a recognized institutionBachelor’s/ Master’s degree in computer science, mathematics, computer engineering, or relevant technical fieldDemonstrable research experience involving data pre-processing and preparation for machine learning modelsDemonstrable research experience in conducting experiments for training and evaluating deep neural networksKnowledge of multi-modal learning, transfer learning, transformers, or self-supervised learningExperience in dealing with large medical datasets (e.g., electronic health records data or medical images)Ability to use high performance computing clusterProficient programming experience in Python and libraries (e.g., Pytorch, TensorFlow)Experience in maintaining high-quality code on GithubExperience in running and managing experiments using GPUsAbility to visualize experimental results and learning curvesEffective inter-personal and team-building skillsSelf-motivated with an ability to work independently and in a team to get the work doneExcellent communication skills (oral and written communication)Willingness to learn and confront new challengesPreferred QualificationsBachelor’s/ Master’s thesis conducted in the area of machine learning for healthcare and related topicsFirst-author peer-reviewed published papers (or under review)Evidence of leadership and service activities in the academic domainFor consideration, applicants need to submit a cover letter, curriculum vitae with full publication list, research statement (1-page), project proposal summary (1-page), and three letters of reference, all in PDF format. If you have any questions, please email Prof. Farah Shamout at farah.shamout@nyu.edu.The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be accepted immediately and candidates will be considered until the position is filled. Please visit our website at http://nyuad.nyu.edu/en/about/careers/faculty-positions.html for instructions and information on how to apply.About NYU Abu Dhabihttps://nyuad.nyu.edu/en/NYU Abu Dhabi is the first comprehensive liberal arts and research campus in the Middle East to be operated abroad by a major American research university. Times Higher Education ranks NYU among the top 30 universities in the world, making NYU Abu Dhabi the highest-ranked university in the UAE and MENA region. NYU Abu Dhabi has integrated a highly selective undergraduate curriculum across the disciplines with a world center for advanced research and scholarship. The university enables its students in the sciences, engineering, social sciences, humanities, and arts to succeed in an increasingly interdependent world and advance cooperation and progress on humanity’s shared challenges. NYU Abu Dhabi’s high-achieving students have come from over 120 countries and speak over 100 languages. Together, NYU's campuses in New York, Abu Dhabi, and Shanghai form the backbone of a unique global university, giving faculty and students opportunities to experience varied learning environments and immersion in other cultures at one or more of the numerous study-abroad sites NYU maintains on six continents.NYUAD is committed to upholding a culture of non-discrimination, anti-harassment, dignity, and mutual respect; providing equal access and opportunity; and fostering academic excellence in learning, research, and teaching.Students are drawn from among the world’s best. They are bright, intellectually passionate, and committed to building a campus environment anchored in mutual respect, understanding, and care. The NYUAD undergraduate student body has garnered an impressive record of scholarships, graduate-school admissions, and other global honors. Graduate education is an area of growth for the University; the current graduate student population of over 100 students is expected to expand in the next decade as doctoral programs are developed.Working for NYUADAt NYUAD, we recognize that Abu Dhabi is more than where you work; it’s your home. In order for research staff to thrive, we offer a comprehensive benefits package. This starts with a generous relocation allowance; educational assistance for your dependents; access to health and wellness services; and more. NYUAD is committed to research staff success throughout the academic trajectory, providing support for ambitious and world-class research projects and innovative, interactive teaching approaches. Support for dual-career families is a priority. Visit our website for more information on benefits for you and your dependents.NYUAD is an equal-opportunity employer. We welcome applications from all qualified candidates and seek individuals who will contribute to the excellence and vibrancy of our academic community.Applications are welcome from all qualified candidates. In line with UAE regulations, Emirati candidates are encouraged to apply.Join NYU Abu Dhabi, an exceptional place for exceptional people.NYUAD values belonging and respect; such principles are fundamental to the university’s commitment to excellence. NYUAD is an equal-opportunity employer. We welcome applications from all qualified candidates and seek individuals who will contribute to our vibrant, multidisciplinary research and teaching community. Multidisciplinary research and exceptional teaching in a global campus community are hallmarks of the University’s mission.@WorkAtNYUADEqual Employment Opportunity StatementFor people in the EU, click here for information on your privacy rights under GDPR: www.nyu.edu/it/gdprNYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply for vacant positions at all levels.Sustainability Statement NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu/sustainability

As an AI Researcher at Vatic Labs in Abu Dhabi, you will research and develop innovative AI-driven quantitative trading strategies. You will explore vast amounts of market and alternative data, inventing and applying a new generation of state-of-the-art technologies that are inspired by large language models, deep neural networks, transformers, and advanced prompt engineering methods to discover and capitalize on trading opportunities.The nature of the problems we work on is challenging, hence we hire some of the world's top AI talent to develop novel AI methods and trading strategies. Our team of talented researchers and technologists has been recognized as leaders in their field. Our distinguished researchers have been widely cited for their publications in top-tier, peer-reviewed scientific journals. We are passionate about hiring the best and the brightest, empowering them with the tools and mentorship needed to be successful. Our environment is highly collaborative and open, sharing AI and trading expertise across team members and fostering innovation and growth.If you possess all or most of the following, we would love to explore what is available for you with our team:Earned or will earn a Master's or Ph.D. in a quantitative field, such as Computer Science, Electrical and Computer Engineering, Applied Math, Statistics, Quantitative Finance, Cognitive Science, Physics or another field of science.Experience analyzing large data sets with rigorous statistical and ML/AI approaches, including classification, clustering, regression (linear and nonlinear), optimization, signal processing, filtering and smoothing, time-series analysis, hidden Markov models, high-dimensional data analysis, vector quantization, decision tree methods, EM methods, Bayesian methods, variational inference methods, and neural networks.Demonstration of deep knowledge of large language models and deep neural networks for practical applications (e.g. NLP, vision, speech, signal processing, scientific computing, finance, etc). Finance applications preferred but not necessary.Ability to generate impactful research in academic or professional pursuits.Advanced understanding and experience of practical programming languages and software tools for data analysis and ML/AI applications, such as Python, C++, PyTorch, Tensorflow, etc.Interest and enthusiasm for learning about financial markets (previous experience not required).At Vatic, we're serious about our work—but we also believe in balance, growth, and having fun along the way. Here's what you can expect:Flat structure with direct executive exposure – Work closely with leadership and make an impact from day one.Comprehensive health benefits – Full health insurance coverage for employees and dependents.Daily meals provided – Enjoy free lunch at the office.

Job Title: Data / AI ExpertPosting Date: 7 Jul 2026Requisition ID: 3742Location: HQ - Abu DhabiPosting Status: Active RecruitmentJob PurposeThe Data and AI Engineering Expert is a senior hands-on technical authority responsible for the design, development, and operationalization of enterprise data and AI platforms across ENEC. This role leads the engineering delivery of scalable, secure, and compliant data pipelines, AI/ML solutions, and analytics platforms leveraging technologies such as Databricks (Delta Lake, Unity Catalog, MLflow, Delta Live Tables), Microsoft Azure (Azure Data Factory, Azure ML, Microsoft Fabric, Azure AI Foundry, Copilot Studio), Collibra (Data Governance & Data Quality), Power BI, and OT/industrial data systems including PI System, SCADA, and DCS.The Expert applies deep engineering expertise to architect and deliver production-grade solutions, ensures data governance and quality standards are upheld, and drives the adoption of AI and analytics capabilities that directly support ENEC's mission of safe, innovative, and efficient nuclear energy generation. This role acts as a principal technical contributor and mentor, enabling operational excellence and digital transformation at scale.Key Activities, Responsibility & AccountabilityActivity: Data Engineering Architecture & Platform DevelopmentResponsibilities And Accountabilities: Design, build, and maintain scalable, secure, and high-performance data platforms including Lakehouse architectures using Databricks Delta Lake, Unity Catalog, and Delta Live Tables (DLT). Develop and operationalize robust data pipelines, ETL/ELT workflows, and integration frameworks using Azure Data Factory, Databricks Workflows, and related orchestration tools. Architect and implement data models, semantic layers, and data products that serve enterprise analytics, AI, and reporting needs. Ensure seamless integration of OT and industrial data sources — including PI System, SCADA, and DCS — into enterprise data platforms. Design and implement APIs, data contracts, and integration frameworks to enable enterprise-wide data consumption. Ensure platform scalability, resilience, high availability, and disaster recovery capabilities in compliance with nuclear and regulatory requirements. Apply and enforce data standards, naming conventions, and metadata management practices across all data assets using Collibra and Unity Catalog.Responsibilities And Accountabilities: Design, develop, and deploy production-grade machine learning, deep learning, and generative AI models using Azure ML, MLflow, and Databricks ML. Engineer end-to-end MLOps pipelines covering model training, versioning, validation, deployment, monitoring, and retraining — ensuring reliability and reproducibility. Build and operationalize AI-powered solutions including predictive analytics, anomaly detection, natural language processing (NLP), and GenAI/LLM-based applications using Azure AI Foundry and Copilot Studio. Develop BI and semantic models in Microsoft Fabric and Power BI, enabling self-service analytics and executive reporting across the organization. Apply Responsible AI principles and governance frameworks to all AI and ML solutions, ensuring explainability, fairness, and compliance. Conduct rigorous model evaluation, performance benchmarking, and validation to ensure solutions meet accuracy, reliability, and safety standards. Contribute to the continuous improvement of AI engineering standards, patterns, and reusable components across the enterprise.Responsibilities & Accountabilities (contd.)Activity: Advanced Subject Matter KnowledgeResponsibilities And Accountabilities: Demonstrates deep, hands-on expertise in enterprise data engineering, AI/ML platform development, and cloud-native architectures within highly regulated environments. Maintains current knowledge of global trends in data engineering, MLOps, GenAI, cloud technologies (Azure, hybrid, on-premise), and nuclear industry compliance requirements. Understands the full lifecycle of data and AI platforms including design, development, testing, deployment, monitoring, and decommissioning. Applies comprehensive knowledge of data governance frameworks (Collibra, Unity Catalog), master data management, data quality, and lineage management. Possesses strong awareness of OT/IT convergence, industrial data systems (PI System, SCADA, DCS), and their integration into enterprise analytics environments. Maintains expert-level proficiency in programming languages and frameworks including Python, SQL, Spark, and relevant AI/ML libraries.Activity: Complex Problem Solving & InnovationResponsibilities And Accountabilities: Tackles complex, ambiguous engineering challenges in data platform architecture, AI model development, and system integration — delivering innovative, compliant, and production-ready solutions. Leads root cause analysis and corrective/preventive actions for platform incidents, data quality failures, model degradation, and system disruptions. Develops and implements robust engineering solutions to address performance bottlenecks, scalability constraints, and integration challenges. Navigates conflicting technical requirements, evolving regulatory standards, and stakeholder needs to deliver optimal engineering outcomes. Drives continuous improvement by benchmarking against global engineering best practices, evaluating emerging technologies, and implementing lessons learned.Professional CertificationsMin - Relevant certifications in one or more of: Databricks (Data Engineer Associate/Professional, ML Professional), Microsoft Azure (Data Engineer, AI Engineer, Solutions Architect), MLOps, or Data Governance (Collibra).Pref - Multiple cloud and AI certifications. Microsoft Fabric, Azure AI Foundry, or Databricks Unity Catalog specialty certifications. Industry publications or contributions in data engineering or AI.QualificationsMin - Bachelor’s degree in computer science, Information Technology, Data Management, Engineering, or related discipline.Pref - Master’s degree in a relevant field.ExperienceMin - Minimum 12+ years' hands-on experience in enterprise data engineering, AI/ML platform development, and cloud-native architectures, including production deployment and operations. Experience embedding governance within modern data platforms (preferably Databricks) and integrating SAP/Oracle ERP domains.Pref - Experience in energy, utilities, nuclear, financial services, government, or other highly regulated sectors. Demonstrated AI governance experience (provenance, bias monitoring, model data requirements) in databricks or similar AI/analytics platforms exposure. Demonstrated experience leading large-scale data and AI engineering programs

Job DescriptionThe Department of Mechanical and Aerospace Engineering at the United Arab Emirates University (UAEU) is seeking a highly motivated Postdoctoral Researcher for a 2-year A-TRIP funded project titled: “Smart Aqua-PV: A Solar-Powered Digital Twin and AI-Driven Smart Aquaculture Pilot for Sustainable Protein Production in Arid Environments.” The project integrates solar-powered recirculating aquaculture systems (RAS), IoT monitoring, digital twin modeling, artificial intelligence optimization, and ultra-low-power underwater sensing in collaboration with the Massachusetts Institute of Technology (MIT). The Postdoctoral Researcher will lead the development of AI-driven optimization models and the digital twin framework for the Smart Aqua-PV pilot system. Responsibilities include: Development of digital twin models integrating solar energy, RAS dynamics, and sensor data Design and implementation of AI algorithms for feeding optimization, water quality prediction, and anomaly detection Integration of MIT piezo-acoustic sensing data into the AI framework Simulation of operational scenarios (heat stress, power interruption, system disturbances) Data analytics and predictive modeling using machine learning tools Supervision of graduate students (PhD and MSc) Preparation of high-impact journal publications Contribution to techno-economic analysis and scalability modeling Participation in stakeholder workshops and project dissemination The successful candidate will play a key role in delivering a functional AI-enabled aquaculture platform over the 24-month project period.Minimum Qualification PhD in Mechanical Engineering, Electrical Engineering, Computer Engineering, Energy Systems, AI, or a closely related field Strong background in machine learning and data-driven modeling Experience with Python, MATLAB, or similar computational tools Experience in system modeling and simulation Proven publication record in peer-reviewed journals Ability to manage research tasks independently Strong scientific writing and communication skills.Preferred Qualification Experience in digital twin modeling Experience in IoT data systems or sensor integration Background in renewable energy systems or solar PV Experience in aquaculture systems or environmental monitoring (advantageous but not mandatory) Knowledge of optimization algorithms and agent-based models Experience in real-time control systems Experience working on interdisciplinary or international projects Willingness to collaborate with MIT research teamSpecial Instructions to Applicant A detailed CVEvidence of prior experience in machine learning,system modeling,or energy systemsPDF copies of 2 representative journal publicClose Date Kindly apply before the closing date.01/08/2026ApplyDepartmentDivisionGradePosting NumberPosition Number

About AI71:AI71 is an industry leader in artificial intelligence, delivering innovative solutions that empower developers, businesses and governments to solve complex challenges. AI71 builds secure, enterprise-ready applications powered by cutting-edge technology—tailored for knowledge workers and sector-specific needs. AI71 bridges the gap between advanced AI and real-world impact. Guided by a strong commitment to research and responsibility, we create transformative solutions that drive progress and empower communities.The Role:As a Senior Machine Learning Engineer at AI71, you’ll be responsible for developing, deploying, and optimizing machine learning models and systems that power our AI solutions. You will collaborate with cross-functional teams to translate business challenges into impactful AI products.What You'll Do:Model Development: Develop, train, and deploy predictive models that enhance the capabilities of our AI solutions.AI Technologies: Work with state-of-the-art AI techniques, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), and apply them to real-world business contexts.Cross-Functional Collaboration: Partner with business stakeholders to understand objectives and translate them into actionable machine learning tasks.Model Optimization: Continuously monitor, evaluate, and improve models based on real-world performance and evolving business needs.Data Pipeline Maintenance: Implement and manage robust data preprocessing pipelines to ensure high-quality, reliable input data for model development.What You'll Bring:8+ years of experience in AI, Machine Learning, Reinforcement Learning (RL), Data Science, or a related field.Proven experience with Large Language Models (LLMs) and fine-tuning techniques.Master’s or Ph.D. in AI, Data Science, Computer Science, Statistics, or a related field.Strong proficiency in programming languages like Python or R. Preference for candidates with a competitive coding background (e.g., ACM/ICPC, NOI/IOI, Top Coder, Kaggle).Expertise in machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch), Generative AI technologies, and libraries like Langchain, Weaviate, Langgraph, LlamaIndex.Demonstrated success in applying data science and machine learning to solve real-world, business-critical problems.Excellent communication and collaboration skills with the ability to work across interdisciplinary teams.Family Book for UAE Nationals Strong communication, stakeholder management, and decision-making skills, with a passion for building diverse, inclusive engineering teams. Why AI71:Mission-Driven Work: Work on cutting-edge AI applications with a talented and passionate team, solving real-world challenges in critical sectors.Unparalleled Opportunity: This is a chance to innovate and solve real-world challenges using AI at a company with unique access to world-leading models and resources.Career Growth: We offer competitive compensation, benefits, and significant career growth opportunities as a foundational member of the team.World-Class Environment: Enjoy a flexible working environment and the latest tools & technologies needed to do your best work.

About AI71:AI71 is an industry leader in artificial intelligence, delivering innovative solutions that empower developers, businesses and governments to solve complex challenges. AI71 builds secure, enterprise-ready applications powered by cutting-edge technology—tailored for knowledge workers and sector-specific needs. AI71 bridges the gap between advanced AI and real-world impact. Guided by a strong commitment to research and responsibility, we create transformative solutions that drive progress and empower communities.The Role:As a Senior Machine Learning Ops Engineer at AI71, you'll be responsible for developing, deploying, and optimizing machine learning models and systems that power our AI solutions. You will collaborate with cross-functional teams to translate business challenges into impactful AI products.What You'll Do:Model Development: Develop, train, and deploy predictive models that enhance the capabilities of our AI solutions.AI Technologies: Work with state-of-the-art AI techniques, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), and apply them to real-world business contexts.Cross-Functional Collaboration: Partner with business stakeholders to understand objectives and translate them into actionable machine learning tasks.Model Optimization: Continuously monitor, evaluate, and improve models based on real-world performance and evolving business needs.Data Pipeline Maintenance: Implement and manage robust data preprocessing pipelines to ensure high-quality, reliable input data for model development.What You'll Bring:Master's or Ph.D. in AI, Data Science, Computer Science, Statistics, or a related field.5+ years of experience in AI, Machine Learning, Reinforcement Learning (RL), Data Science, or a related field.Proven experience with Large Language Models (LLMs) and parameter-efficient fine-tuning methods (LoRA, QLoRA, etc.) techniques.Strong proficiency in programming languages like Python. Preference for candidates with a competitive coding background (e.g., ACM/ICPC, NOI/IOI, Top Coder, Kaggle).Experience in building and deploying LLM-powered applications using FastAPI/ Flask and Streamlit for front-end interfaces, solid understanding of REST principles, HTTP Methods, websockets and API lifecycle management;Expertise in machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and libraries like Langchain, Langgraph, LlamaIndex.Experience with SQL, NoSQL (PostgreSQL, MySQL, MongoDB, Redis) and vector databases (Pinecone, Weaviate, pgvector) for structured data storage and semantic search.Demonstrated success in applying data science and machine learning to solve real-world, business-critical problems.Excellent communication and collaboration skills with the ability to work across interdisciplinary teams.Strong communication, stakeholder management, and decision-making skills, with a passion for building diverse, inclusive engineering teams. Why AI71:Mission-Driven Work: Work on cutting-edge AI applications with a talented and passionate team, solving real-world challenges in critical sectors.Unparalleled Opportunity: This is a chance to innovate and solve real-world challenges using AI at a company with unique access to world-leading models and resources.Career Growth: We offer competitive compensation, benefits, and significant career growth opportunities as a foundational member of the team.World-Class Environment: Enjoy a flexible working environment and the latest tools & technologies needed to do your best work.

Role OverviewThis role focuses on designing and building scalable data infrastructure to support advanced autonomous systems. The position is responsible for transforming large-scale multimodal sensor data into high-quality, structured datasets that are ready for downstream processing and machine learning workflows.The work involves establishing foundational systems and architectural decisions that will support long-term scalability, including how data is recorded, ingested, stored, versioned, labeled, and served. The environment handles hundreds of terabytes of data generated from LiDAR, cameras, IMU, GPS, and radar across multiple platforms.Key ResponsibilitiesOn-vehicle data recording pipeline Design and manage high-throughput recording systems, including topic selection, multi-GB/s write pipelines, and efficient data formats (MCAP/rosbag2). Oversee on-platform storage and ensure reliable data transfer to cloud environments with integrity checks. Ensure timestamp accuracy and synchronization across recorded data. Data lake architecture Design and maintain scalable storage solutions across S3, FSx/Lustre, and GCS. Define data organization, regional placement, caching strategies, retention policies, data lineage, and cost optimization. Dataset pipeline development Build pipelines that convert raw sensor data into structured, training-ready datasets. Ensure accurate time alignment across modalities, including ego-pose, calibration metadata, and scenario tagging. Versioning and dataset management Implement robust dataset versioning and discovery processes. Evaluate and deploy tools such as DVC, LakeFS, Deep Lake, and FiftyOne, ensuring datasets are reproducible, traceable, and easily accessible. Dataset format design Contribute to defining efficient on-disk dataset formats, focusing on write performance and optimized I/O for large-scale training workloads. Annotation workflows Develop and manage annotation pipelines, including defining vendor handoff formats, ingesting labeled data, performing quality control, handling schema evolution, and supporting iterative dataset improvements. Required Experience5+ years of experience building production-grade data infrastructure, ideally involving large-scale multimodal or sensor data (e.g., robotics, autonomous systems, geospatial, or scientific domains) Strong proficiency in Python, with the ability to work with C++ for ROS2 and pipeline-related tooling Hands-on experience with cloud storage and distributed systems (S3, GCS, FSx, Lustre), including performance and cost optimization Experience with dataset versioning and ML data tools such as DVC, LakeFS, Deep Lake, FiftyOne, or similar platforms Preferred QualificationsBackground in autonomous systems or mobile platforms, particularly in complex or unstructured environments Experience working with large-scale annotation workflows and external labeling providers Familiarity with distributed training approaches (e.g., DDP, FSDP) to support efficient collaboration with machine learning infrastructure Data Engineer in Abu Dhabi, United Arab Emirates

DeepLight AI is a specialist AI and data consultancy dedicated to transforming the regional corporate landscape through bespoke, high-impact intelligent systems. Based in the UAE, we partner with organizations across diverse sectors—with a deep-rooted expertise in Financial Services and Banking—to bridge the gap between complex data and actionable business strategy.At DeepLight, we don't believe in "off-the-shelf" fixes. We deliver tailored AI solutions designed to integrate seamlessly into existing enterprise architectures, ensuring that innovation is both scalable and secure. From building robust data foundations to deploying sophisticated AI platforms, we empower our clients to lead in an increasingly automated world.As a Senior AI Engineer, you will drive the design, development, and deployment of production-grade Artificial Intelligence and Generative AI solutions. This role sits at the intersection of cutting-edge research and enterprise-scale application engineering, specifically focused on delivering high-impact, secure, and performant intelligent systems for premier clients in regulated spaces like financial services and banking.You will act as a technical pillar within the AI squad—collaborating with Data Architects, UI Engineers, and delivery leads to transform complex business requirements into robust, production-ready AI agents and pipelines. This role demands exceptional technical mastery, a deep commitment to architectural integrity, and a proactive approach to solving ambiguous data challenges.Key ResponsibilitiesGenerative & Agentic AI EngineeringCognitive Systems Architecture: Design, build, and optimize enterprise-grade Generative AI applications and multi-agent frameworks capable of complex reasoning and autonomous task executionKnowledge Retrieval Systems: Architect and maintain scalable Retrieval-Augmented Generation (RAG) pipelines utilizing advanced vector databases and semantic search strategiesAdvanced Prompt Engineering: Develop and systematically evaluate advanced prompting techniques, guardrails, and context-window management strategies to ensure predictable, secure model behaviorDeep Learning & Model OptimizationCore Modeling & Execution: Train, fine-tune, and deploy deep learning models across both Natural Language Processing (NLP) and Computer Vision (CV) domainsOpen-Source & Cloud Integration: Evaluate and deploy both proprietary cloud models (e.g., GPT, Claude) and open-source foundation models, balancing performance, latency, and costEdge & Inference Optimization: Convert and optimize models for efficient production deployment and runtime inference using formats like ONNXData & MLOps InfrastructureData Processing Pipelines: Architect and refine complex, highly performant data preprocessing and feature engineering pipelines for unstructured and structured dataDatabase Governance: Design and optimize high-throughput queries across relational SQL databases and specialized NoSQL/Vector data storesRigorous Evaluation: Establish robust, data-driven model evaluation frameworks to continuously benchmark accuracy, drift, latency, and safety in productionAs an AI consultancy, our greatest asset is the expertise of our people.While technical mastery is the foundation of what we do, the ability to bridge the gap between complex data science and actionable business value is what defines your success with Deeplight.We're looking for individuals who are not only world-class in their fields of specialism, but also compelling communicators and persuasive advocates for their own skills.You will be the face of our firm, tasked with building trust, articulating the "why" behind your technical decisions, and effectively "selling" your vision to high-level stakeholders.If you thrive on the challenge of presenting cutting-edge solutions as much as you do on building them, you will fit right in.RequirementsWe need you to have:A proven track record of designing, evaluating, and operating AI/ML models in high-availability enterprise or production environmentsDemonstrated professional or research experience spanning both Natural Language Processing (NLP) and Computer Vision (CV)Hands-on experience leveraging enterprise cloud AI infrastructures (such as Azure AI Studio or AWS Bedrock) to deploy foundation modelsAI, Modeling & FrameworksDeep conceptual and practical understanding of Large Language Models (LLMs), agentic workflows, function calling, and embedding modelsExpert proficiency in PyTorch and TensorFlow for building, training, and troubleshooting deep neural networksA practical understanding of model compilation, quantization, and deployment optimization via ONNX runtimeHigh proficiency in configuring and querying Vector Databases (e.g., Azure DocumentDB, Elasticsearch, Faiss) alongside extensive knowledge of enterprise SQL and NoSQL architecturesSoftware Engineering & Core ToolsPerfect-tier coding skills in Python, with a command of asynchronous programming, design patterns, and clean, modular code architectureAdvanced capabilities in processing massive datasets utilizing standard data ecosystems (e.g., Pandas, NumPy, Polars, or PySpark)It would also be great if you had:An MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a highly related quantitative fieldPrior experience engineering AI solutions within banking, fintech, or highly regulated corporate environments (e.g., familiarity with data privacy, compliance, and secure financial data models)Familiarity with framework libraries such as LangChain, LlamaIndex, or AutoGen for agentic workflow constructionBenefitsThe benefits you'll enjoy as part of this role include:Competitive salary Comprehensive personal health insurance Visa Sponsorship for the successful individualProfessional development and certification supportSubscription reimbursement relating to your roleOpportunity to work on cutting-edge AI projectsMonthly Employee Incentive programCareer advancement opportunities in a rapidly growing AI companyThis position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients.At DeepLight AI, we recognise that diversity drives innovation. We are committed to fostering an inclusive environment where individuals with different thinking styles can thrive and contribute their unique strengths to our specialised AI and data solutions.Our goal is to ensure our application and interview process is accessible, predictable, and fair for all candidates.If you require any specific adjustments to the application process, or if you require any reasonable adjustments should you be successful in being processed to the interview stage, please do let us know. This information will be kept strictly confidential and will not impact hiring decisions.

About Infinite PlInfinite pl is a digital-led tech firm driven to become a digital logistics pioneer by harnessing the power of people, data, and platforms. We orchestrate and build innovative platforms that tackle complex problems within logistics and adjacent sectors, enriching the experiences of governments, businesses, and residents through cutting-edge digital solutions.Role SummaryWe are looking for an AI Engineer who can turn priority use cases into working, evaluable agents. You will design context, tools, prompts, retrieval flows, agent loops, and evaluation bundles, and contribute to reusable agentic patterns that let us scale safely across Fast Track innovation and Production-grade delivery. This is a hands-on builder role for someone who pairs strong software engineering with practical LLM and agentic AI delivery.Key Responsibilities Design and build agentic AI solutions from concept to pilot or production, including agent role definition, autonomy boundaries, tool/data scopes, guardrails, and evaluation criteria Implement agent loops, tool-use patterns, context engineering, retrieval/RAG flows, HITL approval journeys, tracing, telemetry, and audit capture Select and justify models based on latency, cost, residency, reliability, and use-case fit; tune solutions for performance and operational cost Develop reusable Agent JD templates, prompt/context patterns, orchestration patterns, and evaluation assets that can be adopted across teams Partner with governance, platform, and integration teams to make agents gate-ready by design, including prompt-injection, PII leakage, and reliability controls Support complex and multi-agent solutions, including orchestration, memory, retrieval, reasoning, and agent-to-agent composition Move solutions through sandbox, staging, and production promotion paths, ensuring each agent is observable, versioned, tested, and auditable Mentor junior engineers and contribute to a strong engineering culture around quality, speed, learning, and responsible AI deliveryKey Requirements Strong software engineering background in Python and/or C#, with experience building production-grade APIs, services, or cloud-native applications Hands-on experience with LLMs, agent frameworks, and agentic design patterns such as Semantic Kernel, Microsoft Agent Framework / AutoGen, LangGraph, or comparable frameworks Practical experience with RAG, vector search, prompt/context engineering, system prompt design, tool calling, and model evaluation Ability to build and maintain evaluation sets, regression tests, and acceptance criteria for agent behaviour, reliability, and safety Experience integrating APIs, data sources, and tools into AI workflows; comfortable debugging across application, data, and model layers Understanding of cloud-native delivery, observability, CI/CD, secrets management, telemetry, and secure software development practices Strong communication skills with the ability to explain technical trade-offs to product, business, governance, and leadership stakeholdersPreferred Qualifications Azure AI Foundry, Azure OpenAI, Azure AI Search, Functions, Container Apps, Cosmos DB, Redis, OpenTelemetry, or equivalent cloud AI stack experience Experience with bilingual or Arabic/English AI products, evaluation design, and user-facing AI experiences Experience with multi-modal AI, including vision, voice, document intelligence, or video/avatar experimentation Prior work in government, regulated, sovereign cloud, or enterprise environments where auditability and data residency matter Technical leadership or player-coach experience, including mentoring engineers and raising engineering standardsTECH STACK / TOOLSAzure AI Foundry - Semantic Kernel - LangGraph - Azure OpenAI - AI Search - Cosmos DB - Redis - Functions, Container Apps - Eval harness - OpenTelemetryFIRST 90 DAYS SUCCESS At least one agent progresses through the full factory path into production or production-equivalent validation on a real source, with a passing evaluation bundle A reusable Agent JD, prompt/context, or orchestration pattern is contributed to the team library The AI engineering team improves first-time gate readiness through better patterns, testing, and documentationThis role is not. A pure model research role or a platform/landing-zone owner. This role builds working agents and the patterns that make them reliable.We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

AI/ML Engineer (Analytics & ML)Location: Abu Dhabi, UAEWe are looking for an AI/ML Engineer for one of our clients in Abu Dhabi to design, build, and deploy machine learning and advanced analytics solutions that power strategic and operational decision-making across the business.Must-Have Skills (Non-Negotiable)Microsoft Fabric — hands-on production experiencePython in Azure environments (Azure ML, Azure Functions, or similar)TensorFlow — real experience building and training models (not just scikit-learn)What We're Looking ForStrong hands-on experience with Microsoft Fabric, Python ,Azure, and TensorFlowSolid grounding in statistics (hypothesis testing, segmentation, root cause analysis)Experience with Azure Cognitive Services, and MLOps pipelinesAbility to work across the full lifecycle — from model development to business storytellingStrong communication skills; comfortable presenting to non-technical stakeholdersIf you are interested please share your profile : Abishake Kosman: abishake.kosman@tmc-employeneurs.com

Role SummaryStellar Technologies is seeking a Machine Learning Engineer (GenAI) to design, build, and deploy next-generation AI systems combining Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI frameworks.In this role, you will bridge model development and production engineering — developing scalable AI pipelines, integrating real-time APIs, and ensuring high-performance AI services that power enterprise-grade solutions. You will work at the intersection of machine learning, cloud infrastructure, and applied research, collaborating with top engineers and data scientists to deliver intelligent, production-ready AI capabilities.Key ResponsibilitiesDevelop and optimize AI systems leveraging LLMs, RAG, and agentic AI frameworks (LangChain, LangGraph).Build and deploy production-grade ML pipelines with real-time inference and retrieval components.Design and manage APIs and streaming services to integrate AI models into enterprise platforms.Implement containerized, orchestrated deployments using Docker, Kubernetes, and Azure ML.Automate data preprocessing, model training, evaluation, and versioning pipelines.Collaborate with cross-functional teams to integrate models into front-end, analytics, and automation workflows.Ensure governance, compliance, and security of deployed AI workloads.Conduct performance benchmarking and optimize inference latency and cost.Monitor AI systems in production using observability frameworks (logging, metrics, tracing).Participate in architecture discussions to enhance scalability and reliability of AI services.Required Skills & ExperienceStrong hands-on experience with LLMs, RAG, and agentic frameworks (LangChain, LangGraph, Semantic Kernel, etc.).Proficiency in Python, with deep understanding of ML libraries like PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers.Solid experience in API and microservices engineering (FastAPI, Flask).Familiarity with streaming architectures and real-time data handling.Knowledge of cloud platforms (Azure preferred), including Azure AI, Cognitive Services, and ML Ops.Experience with containerization and orchestration (Docker, Kubernetes).Understanding of vector databases (Pinecone, Weaviate, FAISS) and retrieval mechanisms.Experience in CI/CD, model deployment, and production monitoring.Preferred SkillsExposure to GPU-based inference optimization and serverless deployment.Knowledge of observability and monitoring tools for AI (Prometheus, Grafana, Azure Monitor).Experience in model fine-tuning, prompt engineering, or agentic orchestration.Understanding of AI governance, ethical AI, and data privacy frameworks.Soft SkillsStrong analytical and problem-solving mindset.Excellent collaboration and communication skills.Passion for innovation, experimentation, and applied AI.Job Category: Software EngineerJob Type: Full TimeJob Location: Abu Dhabi

Job DescriptionAbout the Role:We are seeking an AI Engineer (Innovation) with 6+ years of experience with dtrong programming experience in Python. Expertise in Machine Learning, Deep Learning, NLP, and Generative AI. Hands-on experience with OpenAI, Azure OpenAI, LangChain, Semantic Kernel, AutoGen, or similar Agentic AI frameworks.RequirementsDesign and develop AI/ML and Generative AI solutions.Build predictive models for demand forecasting, revenue optimization, dynamic pricing, ancillary revenue growth, and passenger behavior analysis.Develop and deploy LLM-based applications using RAG, Vector Databases, Prompt Engineering, and Agentic AI frameworks.Build intelligent recommendation and personalization engines.Develop scalable AI pipelines and integrate AI models with enterprise applications and operational systems.Deploy and manage AI solutions on Azure cloud platforms.Collaborate with Data Engineers, Data Scientists, Product Owners, and Business Stakeholders to translate business requirements into AI solutions.Ensure model performance, scalability, security, governance, and compliance standards.Required SkillsExperience building RAG architectures and Vector Databases.Strong knowledge of LLMs, Prompt Engineering, Fine-tuning, and AI Evaluation frameworks.Experience with Azure AI Services, Azure Databricks, Azure Machine Learning, Azure Data Factory, and Azure DevOps.Experience with MLOps, CI/CD, model deployment, monitoring, and governance.Knowledge of data engineering concepts, APIs, microservices, and event-driven architectures.Familiarity with SQL, Spark, and large-scale data processing.

About Brain Co.Brain Co. is an Applied AI startup founded by Elad Gil and Jared Kushner, and backed by many of Silicon Valley’s leading builders — including Patrick Collison (CEO of Stripe), Andrej Karpathy (Cofounder of OpenAI), Mike Krieger (CPO of Anthropic), Kevin Weil (CPO of OpenAI), and Aravind Srinivas (CEO of Perplexity).We are building an AI platform and applications for the world’s most important institutions - delivering impact on real-world problems.Our progress so farAutomated construction permitting for a sovereign government → 80% faster, unlocking $375M+ in valueOptimized supply chains for a leading global energy company → 30% lower cost, 99% reliability, preventing $100M+ in lossesStreamlined hospital patient care across national health systems → 40% better outcomes, 80% less admin workRaised a $30M Series A from top investorsBuilt a team of 40+ AI experts from Tesla, Google DeepMind, NVIDIA, and DatabricksAt Brain Co., your work will be deployed in the real world, not stuck in research. We move fast, with more demand than we can serve, and are looking for exceptional people to take ownership from day one.About The RoleAs an AI/ML Engineer at Brain Co., you will play a crucial role in deploying state-of-the-art models to automate various real world problems in sectors such as healthcare, government and energy. Part of the role will involve turning research breakthroughs into practical solutions for various nation states. This role is your opportunity to make a significant impact by making AI technology both accessible and influential.In This Role, You WillInnovate and Deploy: Design and deploy advanced LLM models to tackle real-world problems, particularly in automating complex, manual processes in a range of real-world verticals.Optimize and Scale: Build scalable data pipelines, optimize models for performance and accuracy, and prepare them for production. Monitor and maintain deployed models to ensure they continue delivering value across various governments worldwide.Make a Difference: Engage in projects including but not limited to optimizing the world's most advanced energy production systems, modernizing core government workflows, or improving patient outcomes in advanced public healthcare systems. Your work will directly impact how AI benefits individuals, businesses, and society at large.Engage with Leaders: interact directly with government officials in various countries and apply the first of its kind AI solutions while working alongside experienced ex. Founders, AI researchers, and software engineers to understand complex business challenges and deliver AI-powered solutions. Join a dynamic team where ideas are exchanged freely and creativity flourishes. You will be able to wear many hats: software building, product management, sales, interpersonal skills.Learn and Lead: Keep abreast of the latest developments in machine learning and AI. Participate in code reviews, share knowledge, and set an example with high-quality engineering practices.You Might Thrive In This Role If YouHold a BSc/Master’s/PhD degree in Computer Science, Machine Learning, Data Science, or a related field.Have experience building GenAI-focused applications with the latest technologies, including but not limited to Agents, reasoning models and RAG.Have at least a high level familiarity with the architecture and operation of large language models.Have personally implemented models in common ML frameworks such as PyTorch, Jax or TensorFlow.Possess a strong foundation in data structures, algorithms, and software engineering principles.Exhibit excellent problem-solving and analytical skills, with a proactive approach to challenges.Can work collaboratively with cross-functional teams.Thrive in fast-paced environments where priorities or deadlines may compete.Are eager to own problems end-to-end and willing to acquire any necessary knowledge to get the job done.BenefitsCompetitive salary plus equityDaily lunchesCommuter benefitsUnlimited PTOWhy Join UsShip quickly, iterate constantly and see your work deployed at global scaleCollaborate with industry veterans from Tesla, DeepMind, Databricks, and moreAccelerate your career with ownership based on impact, not tenureEarn competitive compensation + meaningful equity in a high-growth companyThrive in a culture built on speed, curiosity, and impactIf you want to see your work deployed at scale with real impact, Brain Co. is the place to build.This is a hybrid role that can be based in either our Abu Dhabi or Doha office

ResponsibilitiesWork with large and complex data sets to solve challenging business problemsCollect, clean, and preprocess large datasets for analysis & model trainingPerform exploratory data analysis (EDA) to uncover insights and inform model developmentDevelop, train, and optimize machine learning models using state-of-the-art algorithms and frameworksBuild end-to-end ML pipelines, including data ingestion, transformation, model training, validation, and deploymentAutomate workflows for model training, testing, and deployment using CI/CD pipelines and MLOps toolsCollaborate with cross-functional teams to integrate models into applications and deliver end-to-end solutionsQualification5+ years of experience in data science, machine learning, or AIExpertise in supervised/unsupervised learning, deep learning, NLP, computer vision, or generative AI (e.g., LLMs).Strong proficiency in Python and/or R; familiarity with SQL for data queryingAbility to build data pipelines (Spark, Airflow, Hadoop) and work with big data toolsUnderstanding of model serving, API development (FastAPI, Flask), and optimizing model performance for real-time or batch inference.Knowledge of Docker, Kubernetes, CI/CD pipelines, and tools like MLflow/Kubeflow for model lifecycle management (MLOps)Experience deploying models on AWS, Google Cloud, Azure, or similar (e.g., Sagemaker, Vertex AI)Educational qualifications: Bachelor’s degree in Computer Science, Engineering, or related field required

Role SummaryAI71 is seeking a Senior Machine Learning Engineer to lead the development and deployment of advanced AI models for the EDGE Group. In this role, you will be responsible for the end-to-end lifecycle of our machine learning systems—from architectural design and data preprocessing to model training, optimization, and production deployment.You will work at the intersection of generative AI and traditional machine learning, building the engines that power two flagship initiatives: LeverEDGE (automated requirements engineering via LLMs) and Intelligent Supply Chain (predictive risk scoring and demand forecasting). Operating within a structured "Sprint Zero" to "Stage Gate" delivery model, you will ensure our models are not just accurate, but also robust, explainable, and deployable within strict defense-grade security environments.Key Responsibilities LLM & NLP Pipelines (LeverEDGE)Regulation Parsing: Design and fine-tune Large Language Model (LLM) pipelines to interpret complex regulatory texts (e.g., military standards, building codes) and extract structured rules.Rule Formalization: Convert natural language requirements into computer-processable formats (e.g., logic tuples) that can be executed by downstream compliance engines.Semantic Search: Implement RAG (Retrieval-Augmented Generation) architectures to enable semantic querying of technical documentation and historical project data.Prompt Engineering: optimize prompt strategies (few-shot learning, chain-of-thought) to improve model performance on domain-specific tasks without extensive retraining. Predictive & Analytical Models (Supply Chain)Forecasting Engines: Develop time-series forecasting models to predict material demand and spend categories, integrating internal ERP data with external market signals.Risk Scoring: Build classification and anomaly detection models to assess supplier risk profiles based on financial health, delivery performance, and geopolitical factors.Optimization Algorithms: Design algorithms for multi-objective optimization (e.g., balancing cost vs. lead time vs. risk) to support procurement decision-making. MLOps & ProductionizationModel Deployment: Containerize models using Docker/Kubernetes and deploy them into secure, on-premise inference environments.Pipeline Orchestration: Build automated training and inference pipelines using tools like Kubeflow or MLflow to ensure reproducibility and scalability.Performance Optimization: Optimize model inference latency and resource usage (e.g., quantization, distillation) to run efficiently on available hardware.Monitoring & retraining: Implement monitoring systems to track model drift and performance in production, establishing feedback loops for continuous improvement.Technical RequirementsCore ML/AI: Expert proficiency in Python and standard ML libraries (PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy).NLP & GenAI: Strong experience with transformer architectures (BERT, GPT, Llama) and NLP frameworks (Hugging Face, LangChain).MLOps: Proficiency with MLOps tools and practices, including containerization (Docker), orchestration (Kubernetes), and experiment tracking (MLflow).Data Handling: Ability to design data preprocessing pipelines for both structured (SQL, tabular) and unstructured (text, PDF) data.Algorithm Design: Strong grasp of algorithmic principles for implementing custom logic, such as graph traversal or geometric computations.Professional QualificationsExperience: 5+ years of experience in Machine Learning Engineering, with a proven track record of deploying models into production environments.Domain Adaptability: Ability to quickly learn and apply ML techniques to specialized domains like defense engineering, supply chain, or construction.Structured Delivery: Experience working in agile environments (Sprints) while adhering to rigorous engineering standards and documentation requirements.Collaboration: Strong communication skills to work effectively with Data Scientists, Backend Engineers, and Domain Experts to align technical solutions with business needs.Why This Role?You will be building the intelligence that drives critical national infrastructure. Your models will not just generate text or predictions; they will directly influence the design of defense systems and the resilience of supply chains. If you are ready to apply advanced ML to tangible, high-stakes problems in a rigorous engineering environment, join AI71.

External Job DescriptionJob Title: Senior AI EngineerQualifications / Education / Experience / TrainingBachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Minimum 3 years of experience in designing and implementing machine learning algorithms. Strong understanding of Data Science, Machine Learning, and Deep Learning, with experience in computer vision. Proficiency in Python and C/C++ is required. Experience working in Linux environments, including shell scripting, and familiarity with Git and Docker.Job Responsibilities (Key Result Areas)Develop software components based on defined requirements and design specifications. Analyze, debug, and resolve software issues on embedded devices and PC-based systems. Perform software integration and ensure proper functioning across modules. Conduct verification activities such as testing, analysis, and reviews to ensure quality and reliability.Collaborate with cross-functional teams to solve complex problems using AI, computer vision, and video analytics techniques. Develop and maintain video analytics solutions on edge devices using Python and C/C++. Implement algorithms for object detection, tracking, recognition, and classification.Ensure compliance with software development standards, quality assurance processes, and configuration management guidelines. Follow company policies, statutory regulations, and safety requirements.Operating EnvironmentWork in a dynamic environment with changing priorities and tight deadlines. Ability to work under pressure and extend working hours when required. Willingness to travel and provide field support during testing. Operate under general guidance from a Manager or Mentor, with responsibility for planning and prioritizing daily tasks.#ADASI

The Haven Lab, in the Division of Engineering and the Center for Cyber Security, New York University Abu Dhabi, invites applications for a Junior Research Scientist position in security and privacy.The lab's mission is to provide individuals with control over their privacy and protection from digital threats. We want to work towards a future where digital services are inherently designed with user privacy and safety at the forefront.Current Research Thrusts InvolveLarge-scale measurements on the web to understand and characterize harmful online phenomena.Development of AI-based countermeasures for security and privacy, especially in on-device settings.Investigation of attacks/defenses on AI-based systems.More information on Dr. Siby’s research is available at https://sandrasiby.github.io/ . The lab website can be found at https://sites.google.com/nyu.edu/haven-labThe successful candidate will engage in research that includes applied machine learning, systems building, and Internet measurements.Key ResponsibilitiesContribute to the lab's research directions and methodologies.Lead and collaborate on high-impact research projects in applied security and privacy.Work with undergraduate students, providing guidance on research projects.Engage with academic and industry partners to advance the lab's research goals.QualificationsA Bachelors in Computer Science, Engineering, or a related discipline. Good programming and analytical skills, and willingness to work with new technologies/systems.Excellent communication skills and the ability to work effectively in a collaborative environment.Preferred QualificationsExperience in cybersecurity/privacy, either within web technologies or applied machine learning.Prior experience working on research projects. Masters in Computer Science, Engineering, or a related discipline.For consideration, applicants need to submit a cover letter, curriculum vitae, statement of research interests, transcript, and at least two recommendation letters, all in PDF format. If you have any questions, please email: sandra.siby@nyu.edu.About NYU Abu Dhabihttps://nyuad.nyu.edu/en/NYU Abu Dhabi is the first comprehensive liberal arts and research campus in the Middle East to be operated abroad by a major American research university. Times Higher Education ranks NYU among the top 30 universities in the world, making NYU Abu Dhabi the highest-ranked university in the UAE and MENA region. NYU Abu Dhabi has integrated a highly selective undergraduate curriculum across the disciplines with a world center for advanced research and scholarship. The university enables its students in the sciences, engineering, social sciences, humanities, and arts to succeed in an increasingly interdependent world and advance cooperation and progress on humanity’s shared challenges. NYU Abu Dhabi’s high-achieving students have come from over 120 countries and speak over 100 languages. Together, NYU's campuses in New York, Abu Dhabi, and Shanghai form the backbone of a unique global university, giving faculty and students opportunities to experience varied learning environments and immersion in other cultures at one or more of the numerous study-abroad sites NYU maintains on six continents.NYUAD is committed to upholding a culture of non-discrimination, anti-harassment, dignity, and mutual respect; providing equal access and opportunity; and fostering academic excellence in learning, research, and teaching.Students are drawn from among the world’s best. They are bright, intellectually passionate, and committed to building a campus environment anchored in mutual respect, understanding, and care. The NYUAD undergraduate student body has garnered an impressive record of scholarships, graduate-school admissions, and other global honors. Graduate education is an area of growth for the University; the current graduate student population of over 100 students is expected to expand in the next decade as doctoral programs are developed.Working for NYUADAt NYUAD, we recognize that Abu Dhabi is more than where you work; it’s your home. In order for research staff to thrive, we offer a comprehensive benefits package. This starts with a generous relocation allowance; educational assistance for your dependents; access to health and wellness services; and more. NYUAD is committed to research staff success throughout the academic trajectory, providing support for ambitious and world-class research projects and innovative, interactive teaching approaches. Support for dual-career families is a priority. Visit our website for more information on benefits for you and your dependents.NYUAD is an equal-opportunity employer. We welcome applications from all qualified candidates and seek individuals who will contribute to the excellence and vibrancy of our academic community.Applications are welcome from all qualified candidates. In line with UAE regulations, Emirati candidates are encouraged to apply.Join NYU Abu Dhabi, an exceptional place for exceptional people.NYUAD values belonging and respect; such principles are fundamental to the university’s commitment to excellence. NYUAD is an equal-opportunity employer. We welcome applications from all qualified candidates and seek individuals who will contribute to our vibrant, multidisciplinary research and teaching community. Multidisciplinary research and exceptional teaching in a global campus community are hallmarks of the University’s mission.@WorkAtNYUADEqual Employment Opportunity StatementFor people in the EU, click here for information on your privacy rights under GDPR: www.nyu.edu/it/gdprNYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply for vacant positions at all levels.Sustainability Statement NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu/sustainability