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AI Implementation Specialist Department: Technology / Operations Reports To: IT HEAD/ COO/CEO Employment Type: Full-Time ________________________________________ About the Role We are looking for a curious, tech-savvy, and proactive AI Implementation Specialist to help drive the company's AI and automation initiatives. This is a hands-on, execution-focused role where you will work closely with different teams to identify manual, repetitive workflows and transform them using AI-powered tools and automation. No team of your own to manage — just real impact through real projects. This is a great opportunity for someone early in their career who is passionate about AI and wants to be at the forefront of how businesses use it day-to-day. ________________________________________ Key Responsibilities AI Project Support & Execution • Assist in the planning, coordination, and execution of AI projects from kick-off to deployment. • Research and evaluate AI tools, platforms, and solutions that fit specific business needs. • Work with vendors and internal stakeholders to integrate AI tools into existing systems and workflows. • Document project progress, timelines, and outcomes to keep stakeholders informed. Workflow Automation • Conduct walkthroughs with department teams (Finance, Purchasing, Operations, Sales, Logistics, etc.) to understand and map out manual processes. • Identify tasks suitable for automation and propose practical AI-driven solutions. • Build and deploy automations using no-code/low-code tools such as Make (Integromat), Zapier, Microsoft Power Automate, or similar platforms. • Monitor and maintain deployed automations, troubleshooting issues and making improvements over time. AI Tools Adoption • Help onboard employees onto new AI tools through simple guides, walkthroughs, and hands-on support. • Act as an internal resource and first point of contact for questions related to AI tools in use. • Stay up to date on new AI tools and use cases, and share relevant findings with the team. Reporting & Documentation • Track key metrics such as time saved, error reduction, and adoption rates for implemented solutions. • Maintain clear documentation of all automations, integrations, and AI workflows. • Prepare simple reports and updates for management on project status and results. ________________________________________ Requirements Must-Have • 1–3 years of experience in a tech, operations, or process improvement role. • Hands-on experience with at least one automation or no-code tool (e.g., Zapier, Make, Power Automate, Notion AI, etc.). • Comfortable using and exploring AI tools (e.g., ChatGPT, Claude, Gemini, or similar). • Strong attention to detail and ability to document processes clearly. • Good communication skills — able to explain tech concepts simply to non-technical colleagues. • Self-starter attitude with a willingness to learn and figure things out. Nice-to-Have • Exposure to basic scripting or programming (Python, JavaScript) — not required but a plus. • Familiarity with project management tools (Asana, Jira, Notion, Trello). • Experience working across multiple departments or in a cross-functional environment. • Understanding of prompt engineering or working with LLM-based tools. ________________________________________ Success Metrics • Number of manual workflows successfully automated within the first 6–12 months. • Time savings and efficiency gains reported by teams using automated processes. • Employee adoption and satisfaction with AI tools introduced. • Quality and completeness of process documentation maintained. ________________________________________

Senior Data Scientist – Large Language Models | Abu Dhabi, UAEPosition OverviewWe are seeking a Senior Data Scientist with strong expertise in large language models (LLMs), agentic workflows, and applied machine learning. This role involves leading the design, training, and deployment of next-generation AI solutions that power intelligent agents, natural language interfaces, and knowledge-driven applications across domains. You will collaborate with cross-functional teams to deliver scalable, high-performance AI systems that unlock value from unstructured and structured data.Key ResponsibilitiesDesign, build, and optimize LLM-based solutions for tasks such as text understanding, summarization, semantic search, dialogue systems, and reasoning.Develop and orchestrate agentic workflows, integrating LLMs with tools, APIs, and data pipelines for autonomous task execution.Fine-tune and align LLMs on domain-specific datasets, leveraging techniques such as RLHF, prompt engineering, retrieval-augmented generation (RAG), and knowledge grounding.Architect multi-modal AI pipelines combining LLMs with computer vision, knowledge graphs, and structured data.Ensure scalability, efficiency, and reliability of deployed models on cloud and edge environments.Stay updated with the latest research in GenAI, agents, and applied AI, translating findings into innovative product features.Collaborate with software engineers, data engineers, and product managers to integrate AI models into production systems.Document methodologies, publish internal best practices, and present findings to stakeholders.RequirementsQualifications• Master’s or Ph.D. in Computer Science, Data Science, Machine Learning, Applied Mathematics, or related field.• Advanced research and practical experience with large-scale machine learning models.• 5+ years of hands-on experience in AI, machine learning, or intelligent agent system development.Experience• Proven experience in developing and deploying LLM-powered solutions.• Strong background in natural language processing (NLP), applied machine learning, and GenAI projects.• Experience with orchestration frameworks (LangChain, LlamaIndex, Haystack, or equivalent).SkillsProficiency in Python and ML frameworks (TensorFlow or PyTorch, Hugging Face).Hands-on with LLM fine-tuning, evaluation, and optimization.Knowledge of RAG pipelines, embeddings, and vector databases (e.g., FAISS, Pinecone, Milvus).Familiarity with agentic architectures and workflow automation frameworks.Familiarity with backend frameworks (e.g., FastAPI), containerization (Docker), and databases (PostgreSQL, Redis).Strong analytical, problem-solving, and research skills.Excellent communication skills to explain technical concepts to diverse audiences.Ability to thrive in fast-paced, collaborative environments.PreferredExperience with multi-agent systems, autonomous reasoning, and planning frameworks.Experience with vector databases (FAISS, Pinecone, Milvus) and orchestration frameworks (LangChain, LlamaIndex, Haystack).Knowledge of Model Context Protocol (MCP) and reasoning models is a plus.Familiarity with responsible AI, bias mitigation, and data privacy in LLM systems.Knowledge of real-time applications (e.g., chatbots, copilots, AI agents). Knowledge of AI coding tools (Cursor, Claude code, OpenAI Codex, github copilot Show more Show less

Join Tether and Shape the Future of Digital FinanceAt Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.Innovate with TetherTether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.But that’s just the beginning:Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET, our flagship app that redefines secure and private data sharing.Tether Education: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.Tether Evolution: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.Why Join Us?Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.Are you ready to be part of the future?About the job:As a member of the AI model team, you will drive innovation in architecture development for cutting-edge models of various scales, including small, large, and multi-modal systems. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field.You will have a deep expertise in LLM architectures, a strong grasp of pre-training optimization with a hands-on, research-driven approach. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements: data curation, strengthening baselines, identifying and resolving existing pre-training bottlenecks to push the limits of AI performance.Responsibilities:Conduct pre-training AI models on large, distributed servers equipped with thousands of NVIDIA GPUs.Design, prototype, and scale innovative architectures to enhance model intelligence.Independently and collaboratively execute experiments, analyze results, and refine methodologies for optimal performance.Investigate, debug, and improve both model efficiency and computational performance.Contribute to the advancement of training systems to ensure seamless scalability and efficiency on target platforms.A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).Hands-on experience contributing to large-scale LLM training runs on large, distributed servers equipped with thousands of NVIDIA GPUs, ensuring scalability and impactful advancements in model performance.Familiarity and practical experience with large-scale, distributed training frameworks, libraries and tools.Deep knowledge of state-of-the-art transformer and non-transformer modifications aimed at enhancing intelligence, efficiency and scalability.Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment. Show more Show less

PurposeThe Data & AI Manager is responsible for defining and executing EIA's data, analytics, and artificial intelligence agenda toenable data-driven decision-making across investment and corporate functions.Operating within a sovereign wealth fund context, the role focuses on building scalable data platforms, advancedanalytics capabilities, and AI use cases that support investment performance, risk management, strategic planning, andoperational efficiency, while ensuring strong governance, data quality, and responsible AI use. The role focuses on AI andanalytics value creation, prioritisation, and adoption, working in partnership with IT for platform delivery and operations.Strategic Responsibilities Define and lead EIA's Data & AI Strategy, ensuring alignment with the Digital Strategy, investment priorities,and corporate strategy. Establish enterprise-wide data governance frameworks, including data quality standards, ownership models,and analytics principles. Identify, prioritize, and sequence AI and advanced analytics use cases that deliver measurable business value Promote data literacy and adoption across investment and corporate teams to embed data-driven decisionmaking Act as a strategic partner to senior leadership on data, analytics, and AI-enabled insightsCore Responsibilities Data Architecture & Analytics Platforms Define data and analytics requirements, standards, and target‑state architecture in collaboration with IT andenterprise architecture. Ensure data and AI solutions meet business requirements for scalability, security, and governance, incoordination with IT. Oversee data ingestion, transformation, and modelling to support analytics and reporting needs, with technicaldata pipeline development and engineering owned by IT. Analytics, AI & Decision Support Own the end‑to‑end AI use‑case lifecycle, including identification, prioritisation, business case development, value measurement, and adoption Develop dashboards, predictive models, and decision-support tools for investment, strategy, risk, and performance teams Lead the delivery of AI-enabled solutions, including advanced analytics, forecasting, and pattern detection Ensure AI use cases are aligned with business objectives and supported by reliable data foundations Technical build and platform operations are delivered jointly with IT and external partners Data Governance & Quality Ensure data quality, lineage, consistency, and transparency across enterprise systems Implement data standards, controls, and monitoring mechanisms to support governance and audit requirements Support responsible and ethical use of AI, including transparency, explainability, and appropriate human oversight Develop AI acceptable‑use guidelines, human‑in‑the‑loop principles, and AI literacy programmes in partnership with Risk, Compliance, and HR Stakeholder Collaboration & Enablement Partner with IT and business stakeholders to implement analytics and AI solutions Translate business needs into data and AI requirements and ensure solutions are adopted effectively Support strategic initiatives through advanced analytics and insight generationPeople & Capability Responsibilities Build and develop data and analytics capabilities across teams Establish knowledge-sharing practices, standards, and best practices for analytics and AI adoption Support capability uplift through training, tools, and data literacy initiativesKey Deliverables Enterprise data platforms and standardized analytics dashboards AI use cases supporting investment research, risk analysis, performance measurement, and strategic planning Data governance frameworks, policies, and standards Insight-driven support for strategic and investment initiativesRequirementsEducation & Qualifications Bachelor's or master's degree in data science, Computer Science, Engineering, Statistics, or a related fieldExperience Requirements 8-12 years of experience in data, analytics, or AI roles within complex organizations Experience within sovereign wealth funds, asset owners or investment managers strongly preferred Proven experience delivering enterprise analytics platforms and AI-driven solutions Strong understanding of data platforms, cloud-based analytics, and machine learning conceptsTechnical Expertise / Skills / Knowledge Data architecture, analytics platforms, and reporting tools AI and machine learning concepts and practical applications Data governance, quality management, and metadata practices Cloud-based data ecosystems and modern analytics stacks Strong ability to translate complex data insights into business-relevant outcomes Excellent stakeholder engagement and communication skills Show more Show less

Hays is working with a leading organisation building enterprise‑scale AI platforms used at pace and at scale.We’re looking for a senior AI/ML to own the MLOps & LLMOps backbone — from CI/CD and cloud infrastructure to production deployments and operational reliability. Why this role?Own end‑to‑end MLOps / LLMOps for high‑impact AI productsDefine the “golden path” for deploying and operating AI safely in productionWork with cutting‑edge AI stacks across Azure, Kubernetes, and GPU workloadsAct as the technical authority for production‑ready AI What we're looking for:8–10 years in DevOps / SRE / ML EngineeringStrong Azure, Kubernetes, CI/CD, IaC experiencePython and modern MLOps know‑howMicrosoft DevOps certification (required) If you want to shape how AI is built, deployed, and trusted at scale, this is a standout opportunity. Show more Show less

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: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. Show more Show less