Machine Learning Engineer

We have partnered with a fast-scaling technology business in the UAE to hire a Machine Learning Engineer. This is a team working on the hard end of applied AI: fine-tuning foundation models, building agentic systems that take real actions, and pushing inference to run faster and cheaper on serious GPU infrastructure. The models you build will be live in production, used by real customers and measured on commercial outcomes.This role suits an engineer who wants to work with the current generation of ML tooling, not maintain a legacy pipeline. You will have the compute, the data and the autonomy to do it properly.About the role:Fine-tune and adapt open-source and proprietary foundation models using techniques such as LoRA, QLoRA, DPO and RLHF, including multilingual and Arabic language use casesBuild and ship production agentic systems with tool use, multi-step reasoning, retrieval and orchestrationOptimise inference for latency and cost using quantisation, distillation and serving frameworks such as vLLM and TensorRT-LLMDesign evaluation frameworks that measure model quality, safety and drift in live environmentsBuild the MLOps backbone covering training pipelines, experiment tracking, model registries, CI/CD for ML and monitoring on GPU infrastructureWork with product and engineering teams to turn business problems into ML systems that ship and move the numbersAbout you:5 years of hands-on experience in machine learning engineering, with a track record of deploying models into productionStrong Python and deep experience with PyTorch, plus Hugging Face Transformers or equivalentPractical experience with LLMs in production, including fine-tuning, RAG and evaluationSolid grounding in MLOps and cloud ML platforms on AWS, Azure or GCPExperience with model serving and inference optimisation, or a clear appetite to go deep on itExposure to multimodal models, distributed training or GPU cluster work is a strong advantageBased in the UAE or willing to relocate