> Markdown version of [/jobs/ext/2255866-ai-ml-infrastructure-engineer](https://www.wearedevelopers.com/jobs/ext/2255866-ai-ml-infrastructure-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# AI/ ML Infrastructure Engineer

- **Company:** OpenSourced
- **Location:** Bristol, UK
- **Salary:** £110,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Continuous Integration, Distributed Computing Environment, Distributed Systems, Python (Programming Language), Machine Learning, Robotic Automation Software, Pytorch, Machine Learning Operations, Terraform, Software Version Control, Data Pipelines, Docker
- **Published:** August 26, 2026
- **Apply:** https://www.collegerecruiter.com/job/2815164237-ai-ml-infrastructure-engineer

## About the Role

* 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, * Work on real-world AI systems deployed into physical robots
 * Direct impact on cutting-edge robotics capability
 * Fast-moving, high-calibre engineering environment

## 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


## Related Videos

- [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered)
- [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding)
- [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon)
- [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops)
- [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker)
- [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning)

## Related Articles

- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)
- [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)
- [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)
- [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)
- [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)