Senior Research Engineer, ML Systems

We are looking for a Senior Research Engineer to join our AI Research team in London. You will work on the the technology, systems and infrastructure that power our frontier research, from accelerators and distributed training pipelines to experiment frameworks and the tooling that lets a small team operate at scale.

You will sit within the research team, understand the science, and make decisions that directly shape what research is possible. The best research engineers change what experiments the team can run and how fast ideas move from whiteboard to result.

We train large-scale models on the world’s richest biological datasets. The engineering challenges are unique: custom architectures on novel data modalities, training runs that push hardware limits, and a pace of experimentation that demands robust and flexible tooling. You will be the person who makes all of that work reliably, and who figures out how to make it work better.

You’ll report to the Head of AI Research and work closely with researchers covering genomics, computational biology, and large-scale deep learning. You’ll also collaborate with the broader platform engineering and data teams across the company.

PhD in computer science, physics, mathematics, or a related field, or equivalent depth of experience gained through years of building ML systems at scale.

You have worked at a frontier research lab where research engineers are treated as first-class contributors. You understand how to run large-scale experiments and you’ve been part of making that actually happen at scale.

You are comfortable across the full stack of ML systems: distributed training frameworks, GPU/accelerator optimization, data pipelines, experiment tracking, and making research reproducible and reliable. You may have experience down to the level of CUDA kernels, and/or you may operate more at the framework and orchestration layer.

You care about research outcomes as much as system uptime. You form opinions about what experiments to run and how to design them. You can read papers and research reports and figure out what it would take to implement them as efficiently as possible.

A backround in mathematics or physics is strongly preferred. The best research engineers bring quantitative intuition to system design decisions.

You have strong software engineering practices: clean code, good testing habits, and an instinct for building systems that other people can actually use. In a small team, the infrastructure you build is the infrastructure everyone depends on.

You are genuinely curious about biology. The data you’ll work with encodes billions of years of evolution, drawn from ecosystems most datasets never touch. You should find that interesting, not incidental.

Low ego, collaborative instincts, and a startup mentality. You’re comfortable with ambiguity and happy to wear multiple hats in a team where everyone contributes beyond their job description. Nice to Have

Experience with biological data: genomic sequences, protein structures, molecular data, or similar.

Familiarity with our broader tech stack: Kubernetes, Dagster, or similar orchestration and infrastructure tools.

Contributions to open-source ML frameworks or research codebases.

• Impactful Mission: This is a rare chance to do work that genuinely matters. You’ll join a talented, fast-moving team, access unique biological datasets at scale, and see your contributions shape real breakthroughs in AI and curative therapeutics..
• Collaborative Culture: You’ll be surrounded by world-class engineers, scientists, and researchers who care deeply about their work and about each other. With offices in London and Boston, we’ve built a flexible, cross-functional environment where personal development and real ownership aren’t just talking points.
• High Growth: We truly believe in investing our people we make coaching available to team members during steep growth journeys and we have twice yearly promotion opportunities. People who are really successful here own it and go directly to solve problems at pace and we ensure reward increases with impact.
• Comprehensive Benefits: We’ve built a benefits package people value. That means competitive salary, equity, and private healthcare with no medical history exclusions so strong that means most employees’ family members opt into our plan over their own. We also offer Carrot Fertility with IVF stipend, salary sacrifice pension, bike to work scheme, life insurance, and more.

Basecamp Research is dedicated to solving major challenges in the life sciences by exploring Beyond Known Biology. Our teams build frontier AI models using BaseData, the world’s largest ethically-sourced and globally representative biological dataset. Our Global Research Team collects and curates our own biological data through partnerships with more than 152 organizations in 28 countries, giving its AI access to genetic diversity that doesn’t exist for models trained on public database sources. This enables Basecamp Research to design novel protein sequences and biological systems that can accelerate therapeutic research and development.

In October 2024 we closed Series B and in January 2026 finalised pre-Series C investment from NVIDIA. With hubs both in London, UK as well as Boston Massachusetts, USA and partners with biopharma companies and academic institutions worldwide, our work has been recognized with honors including Fast Company’s Top 10 Most Innovative Companies in Biotech and the FT-backed Sifted AI100 list of Europe’s leading AI startups.

At Basecamp Research, we pride ourselves on being a diverse, exciting, fun, and flexible place to work. Our team of biologists, engineers, ML scientists, field explorers, and operations specialists are united by a sense of adventure and the belief that nature has already designed the solutions to our planet’s greatest challenges. If you feel passionate about the power of biology, data, and AI to build a better world, we’d love to hear from you.