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# Software Engineer (ML Infrastructure)

- **Company:** Isomorphic Labs
- **Location:** London, UK
- **Contract:** Permanent contract
- **Skills:** Python (Programming Language), Google Cloud, Multi-Cloud, Kubernetes
- **Published:** September 25, 2026
- **Apply:** https://startup.jobs/software-engineer-ml-infrastructure-london-isomorphic-labs-7836972

## About the Role

* Demonstrated ability to independently identify opportunities, deliver solutions and work effectively in cross-functional teams
 * Experience building and evolving infrastructure or platforms at significant scale
 * Strong Python programming (though familiarity with any particular library is not required), * Domain knowledge of ML inference, training or research infrastructure
 * Strong hands-on experience building for Kubernetes
 * Experience providing platforms to internal customers
 * Experience with Google Cloud Platform (GCP)
 * Experience with multi-cloud environments

## Description

This is an exciting opportunity for a small number of innovative and versatile software engineers to work in a fast-paced and research-centric environment.

You will collaborate extensively with internal engineering and research teams to evolve the foundational infrastructure that makes it easy to train and deploy novel machine learning models over vast (and growing) pools of compute and data.

For this role we are looking for individuals with experience of designing and evolving complex systems at significant scale. Domain knowledge of ML inference, training or research infrastructure will be a strong advantage, though we encourage applications from candidates with a record of exceptional impact in any field.

What you will do

 * Evolve the ML infrastructure platform to accelerate both human and agent-driven research at scale
 * Explore options to deploy agents to increase the robustness and reliability of the platform
 * Develop the platform to enable the next generation of distributed, performance-critical training and inference workloads
 * Partner closely with engineering, research and product teams to identify and deliver impact


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