RL Scientist: Biological Discovery & Research Systems

Applied Geometry; Greater London; On-site; GBP 120,000 - 180,000; Full time

Benefits offered by this job

Equity package

Private medical & dental coverage

Equipment budget

Conference funding

Flexible time off

Job summary

Applied Geometry is hiring for a role focused on advancing AI biology through reinforcement learning and agentic systems. You will train agents, build environments, and define evaluation methods to distinguish real progress from shortcuts.

Collaboration with scientists and engineering leadership will shape the stack and culture to accelerate discovery. The position targets ambitious researchers who thrive in ambiguity and pursue impactful, long-horizon problems in biology, drug discovery, and

Qualifications

• Proven ability to operate in ambiguity and own hard problems.
• Strong foundations in reinforcement learning and post-training methods.
• Excellent software engineering skills across the stack, incl. debugging at scale.
• Ability to design experiments and interpret results rigorously.
• Experience building agentic systems or tool-use for long-horizon tasks.
• Curiosity to learn biology and translate questions into measurable goals.

Responsibilities

• Train AI agents with reinforcement learning to tackle long-horizon biology research problems.
• Create RL environments where agents reason over biological data and design experiments.
• Develop reward functions and evaluation to ensure real scientific progress.
• Build scalable infrastructure for large-scale agent rollouts and training.
• Own the full research loop from experiments to reproducible improvements.
• Collaborate with scientists to translate questions into verifiable objectives.
• Help define Applied Geometry’s technical stack and engineering culture.
• Contribute to building biological superintelligence for accelerated discovery.

Skills

High agency

Deep RL

Engineering excellence

Research judgement

Agentic systems experience

Scientific curiosity

Tools

Distributed systems

GPU performance

Job description

Applied Geometry is hiring for a role focused on advancing AI biology through reinforcement learning and agentic systems. You will train agents, build environments, and define evaluation methods to distinguish real progress from shortcuts.

Collaboration with scientists and engineering leadership will shape the stack and culture to accelerate discovery. The position targets ambitious researchers who thrive in ambiguity and pursue impactful, long-horizon problems in biology, drug discovery, and