Job Description

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

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