Machine Learning Engineer – Lumen Enterprise Models (SWE-focused LLMs)

Job title: Machine Learning Engineer – Lumen Enterprise Models (SWE-focused LLMs)Location: London; full in-office working as defaultStart date: ASAPReports to: CEOCompensation: Salary and Equity options available for discussionApplication deadline: 08/11/26 at 23:59 UK time___________________________________________________________________________Help train the software engineers of the futureCosine is building autonomous software-engineering systems for organisations where reliability, security and control matter most.

Our Lumen Enterprise models are designed to work across real codebases.

They need to understand unfamiliar architectures, make changes across multiple files, use tools, run tests and produce software that engineers can maintain and trust.

We’re looking for a Machine Learning Engineer to help train and improve these models.

You’ll work across the full training stack, including pre-training, supervised fine-tuning and reinforcement learning.

This is a truly unique role that will provide exposure across all areas of the model training lifecycle.

WE’re looking for someone who is just as happy to profile the training loop, identifying performance bottlenecks and memory leaks, as implementing new RL algorithms.

This is a hands-on role for someone who enjoys working close to the model and cares.

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the quality of the software it produces.___________________________________________________________________________The roleYou’ll work closely with research, infrastructure and product to answer questions such as:What should Lumen learn next?Which data and environments will teach it most effectively?How should we reward correct, maintainable and useful software?How do we train models to work across large repositories and long contexts?How do we know when a model is genuinely better for engineers?The models you train will write code, use development tools, run tests and receive feedback from real software-engineering environments

Your work will directly influenc.