Senior Research Engineer
Senior Research Engineer (AI)
London | hybrid (3 days on-site)
The client
Our client is on a mission to solve some of the biggest challenges in the life sciences by going beyond what is known in biology. They build frontier AI models using one of the world's largest ethically sourced and globally representative biological datasets, built through an extensive network of research partnerships spanning multiple continents.
They're well funded, having recently closed a significant round backed by a major strategic investor, and they've been recognised on several prominent industry lists celebrating the most innovative companies in biotech and AI.
Their team of biologists, engineers, ML scientists, field explorers, and operations specialists are all united by one belief: nature has already worked out the solutions to our planet's biggest problems. If that excites you as much as it excites them, keep reading.
The Role
As Senior Research Engineer, you'll join their AI Research team in London and work on the technology, systems, and infrastructure that power frontier research, everything from accelerators and distributed training pipelines through to experiment frameworks and the tooling that lets a small team operate at real scale.
You'll sit within the research team itself, not off to the side of it, so you'll understand the science and make decisions that directly shape what research is possible and how fast it moves. You'll work closely with researchers across genomics, computational biology, and large-scale deep learning, as well as the broader technical teams.
What you'll be doing
- Building and maintaining the distributed training pipelines and infrastructure behind large-scale model training on some of the world's richest biological datasets
- Working on custom architectures for novel data modalities, optimising down to the level of CUDA kernels or XLA when needed
- Owning experiment tracking and reproducibility, so research results are robust and trustworthy
- Reading papers and research reports and figuring out what it would actually take to implement them efficiently
- Forming genuine opinions on what experiments should be run and how they should be designed
Essential
- PhD in computer science, physics, mathematics, or a related field, or equivalent depth of experience gained building AI systems at scale
- Experience at a frontier AI research lab where research engineers are treated as first-class contributors, running large-scale experiments as part of that
- Comfortable across the full stack: distributed training frameworks, GPU/accelerator optimisation, data pipelines, experiment tracking
- Contributions to open-source projects like PyTorch, JAX, MLX, or similar
- Strong software engineering fundamentals: clean code, good testing habits, a focus on performance
Nice to have
- Experience with biological data: genomic sequences, protein structures, molecular data
- Familiarity with Kubernetes, Dagster, or similar orchestration tools
- Publications at major venues like NeurIPS, ICML, ICLR, or JMLR
Apply now or drop me a message if you'd like to discuss the role further.
Keywords: Senior Research Engineer, Research Engineer, AI Research, Distributed Training, GPU Optimisation, CUDA, XLA, PyTorch, JAX, Machine Learning Infrastructure, Genomics, Computational Biology, Biotech, London