Research Engineer

Research Engineer focuses on turn research directions into projects: scoping, experiment design, implementation, data, and results.

What the role involves

• Turn research directions into projects: scoping, experiment design, implementation, data, and results.
• Define which metrics matter for agent system performance and which proxies are actually honest.
• Build the evaluation infrastructure: benchmarks, harnesses, and the tooling around them.
• Develop the research agent stack: memory, in-context learning.
• Test-time compute, and models.
• Fine-tune and post-train open models to improve agent performance.

Skills and requirements

• Experience building ML/AI systems in a research-adjacent context, industry, lab, or PhD.
• Experience building LLM-powered systems: prompts, context engineering, agent architectures.
• Experience with evaluations and benchmarks, including tasks where "correct" is ambiguous.
• Familiarity with model training, including the data, optimisation, and evaluation work around it.

Confirmed role details

• London, UK | Full-time.

Candidate fit

• technical judgement, safe working habits, careful diagnostics, and practical problem-solving

Additional role context

• Work closely with biologists, scientific contractors, and the broader team, and act as the technical sparring partner on what to build next.