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Senior Research Engineer - AI for Biology

Cubiq Recruitment United Kingdom
Visa Sponsorship Relocation
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AI Summary

Build and optimize distributed training systems for frontier-scale foundation models trained on proprietary biological datasets. Own GPU optimization, experiment frameworks, and tooling that enables research teams to push hardware limits. Requires full-stack ML engineering expertise and strong software engineering habits.

Key Highlights
Own distributed training pipelines, GPU optimization, and experiment frameworks for frontier-scale AI research
Work with proprietary biological datasets larger and more diverse than any public alternatives
Report to Head of AI Research and shape experimental capabilities at a frontier lab
Key Responsibilities
Build distributed training pipelines for foundation models
Optimize GPU performance and CUDA/Triton/XLA implementations
Develop experiment frameworks and tooling for frontier-scale research
Customize architectures for new biological data types
Push hardware limits with large-scale training runs
Technical Skills Required
Distributed training frameworks GPU performance optimization CUDA/Triton/XLA level engineering
Benefits & Perks
£130,000 to £230,000 base salary
Equity compensation
Relocation support including visa sponsorship

Job Description


Senior Research Engineer | AI for Biology

Central London · On-site · £130,000 to £230,000 base + equity

Relocation support provided, including Visa Sponsorship for candidates working at a frontier lab offices based out of the UK.


Build the training systems behind foundation models trained on data no other lab has.


I'm working with a London AI research company that trains large foundation models for the life sciences. They own a biological dataset that is bigger and more diverse than anything public. They collected it themselves from environments most datasets never touch. Big Tech labs cannot copy their models by throwing compute at public data, because the data itself is the moat that took years to secure. This is truly a herculean task.


Compute is not a bottleneck. The research team runs like a frontier lab rather than a typical biotech and we're looking to add multiple hires.


The role


You will own the systems that power their research: distributed training pipelines, GPU optimisation, experiment frameworks, and the tooling that lets a team work at frontier scale. You sit inside the research team and report to the Head of AI Research. Your decisions shape what experiments are possible and how fast ideas move from whiteboard to result. Custom architectures on new data types. Training runs that push hardware limits. A pace of experimentation that demands robust, flexible tooling.


What they want


  • Industry experience at an AI lab where research engineers are key contributors. They have been clear that this search favours people from industry over purely academic backgrounds.
  • Full-stack depth: distributed training frameworks such as Megatron-LM, DeepSpeed or FSDP, GPU performance work, and experience down to the CUDA, Triton or XLA level.
  • Contributions to open-source ML frameworks or research codebases. They genuinely value this.
  • Strong software engineering habits. Clean code, good tests, a focus on performance, and systems other people can build on.
  • Real curiosity about biology. You do not need bio experience, but the prospect should excite you.


Pay and process


£130k to £230k base depending on experience, plus meaningful equity. They will stretch above the top of the band for an exceptional candidate from a frontier lab. The interview process is rigorous so before the technicals candidates will have a more informal chat with the Head of Research before fully commiting. Expect a technical round on ML fundamentals, hands-on coding, and end-to-end systems design.


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