AI/ ML Infrastructure Engineer

AI / ML Infrastructure Engineer (MLOps) – Robotics - Hybrid in Bristol - Upto £110,000 We’re working with a cutting-edge robotics company building intelligent systems capable of learning real-world physical tasks. They’re now hiring an AI / ML Infrastructure Engineer to own the end-to-end infrastructure that powers model training, data pipelines, and deployment into real-world robotic systems. This is a highly technical role sitting at the intersection of machine learning, distributed systems, and robotics - not a generic MLOps position. Key Responsibilities Build and scale GPU-based training infrastructure for large ML workloads Develop robust data pipelines for multi-modal datasets Own experiment tracking, model versioning, and reproducibility Design and optimise model deployment pipelines (including edge inference) Improve CI/CD workflows for ML systems and automate infrastructure Key Requirements Strong Python and experience with PyTorch-based training pipelines Experience with distributed training (DDP, FSDP, DeepSpeed) Solid cloud experience (GCP / AWS / Azure) Hands-on with Docker and infrastructure-as-code (Terraform) Experience building ML pipelines in production environments Robotics, autonomous systems, or embodied AI experience Benefits Work on real-world AI systems deployed into physical robots Direct impact on cutting-edge robotics capability Fast-moving, high-calibre engineering environment #J-18808-Ljbffr