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# ML Infrastructure Developer (Python/Rust) - Up to £200k base + Bonus + Benefits- London

- **Company:** Hunter Bond
- **Location:** Greater London, UK
- **Experience:** Experienced
- **Salary:** £200,000.0
- **Contract:** Permanent contract
- **Skills:** Distributed Systems, Python (Programming Language), Machine Learning, Tensorflow, Information Technology, Machine Learning Operations, Data Pipelines
- **Published:** September 8, 2026
- **Apply:** https://www.collegerecruiter.com/job/2856365298-ml-infrastructure-developer-pythonrust-up-to-200k-base--bonus--benefits-london

## About the Role

* 4 + Years working with Python and/or Rust - other systems level knowledge a big plus
 * Experience working with highly distributed and scalable systems
 * Strong understanding of high level system design
 * Outstanding academic background - Ideally Computer Science Degree from an Ivy League University
 * A curious and tech driven personality!

## Description

We are seeking an ML Infrastructure Engineer to join a fast-growing team focused on optimising the performance and scalability of machine learning systems.

In this role, you will design and build the infrastructure that powers high-performance ML workloads, enabling faster training, efficient inference, and scalable deployment across distributed environments. You'll work on systems that sit at the intersection of machine learning and high-performance engineering, helping to push the boundaries of model efficiency and throughput.

You will collaborate closely with ML engineers, researchers, and platform teams to identify performance bottlenecks and implement optimisations across the stack-from data pipelines and compute orchestration to model execution and hardware utilisation. Your work will directly impact how models are trained, deployed, and scaled in production environments.

As an early member of a growing team, you'll have significant ownership over architectural decisions, contributing to the design of robust, scalable infrastructure and developer tooling. You'll also help establish best practices around observability, reliability, and performance benchmarking.

This is an ideal opportunity for someone who enjoys low-level problem solving, distributed systems, and working with modern ML frameworks and infrastructure technologies. You'll play a key role in building systems that make machine learning faster, more efficient, and more cost-effective.


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