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About the Role
Applied Geometry is an AI research lab focused on building biological superintelligence to accelerate scientific discovery in biology and health. We are training frontier models to perform scientific research, reason from incomplete evidence, generate and test hypotheses, and pursue complex research programs.
Responsibilities
- Train AI agents through reinforcement learning to solve complex, long-horizon problems in biology and scientific research.
- Build challenging RL environments for agents to reason over biological data, use scientific tools, generate hypotheses, design experiments, and interpret results.
- Develop reward functions and evaluation frameworks that distinguish genuine scientific progress from shortcuts and reward hacking.
- Build scalable infrastructure for agent rollouts, distributed training, and evaluation.
- Own the full research loop: design experiments, implement methods, diagnose failures, and turn promising results into reproducible improvements.
- Work closely with scientists to translate difficult biological questions into tasks with meaningful objectives and verifiable outcomes.
- Help define Applied Geometry’s technical stack, research standards, and engineering culture.
Requirements
- High agency: thrive in ambiguity, move fast, and take ownership of hard problems.
- Deep RL and post-training expertise: understand reinforcement learning from first principles and have hands-on experience training models or agents.
- Exceptional engineering ability: turn research ideas into reliable, performant code.
- Research judgement: design experiments that answer important questions, identify why an approach is failing, and decide what to try next.
- Experience building agentic systems: ideally, worked on tool use, multi-step reasoning, RL environments, or training agents to complete long-horizon tasks.
- Scientific curiosity: desire to build intelligence that can do consequential scientific work.
- Intellectual curiosity and the ability to learn quickly are essential.
Skills
- Reinforcement Learning
- Deep Reinforcement Learning
- Agent Training
- RL Environments
- Reward Design
- Scalable Infrastructure
- Distributed Training
- Debugging
- Tool Use
- Multi-step Reasoning
Location
- Remote
Work Type
- Full-time
Experience Level
- Early hires
Salary/Compensations
- Competitive, top-of-market compensation
Benefits
- Significant equity package
- Comprehensive private medical & dental coverage
- Significant budget for equipment, research tooling, software, and infrastructure
- Access to compute and petabytes of proprietary biomedical data
- Opportunities to attend leading AI, biology, and scientific conferences (fully-funded)
- Regular team meals
- Stocked office
- Working environment designed for elite performance
- Flexible time off with no strict limits
About the Company
- Applied Geometry is an AI research lab building biological superintelligence.
- Our ambition is to compress years of scientific discovery into days and transform our ability to understand and cure disease.
- We're training frontier models to do science across biology, drug discovery and clinical medicine.
- We believe the next frontier of AI requires systems that can reason from incomplete evidence, generate and test hypotheses, and pursue complex research programmes.
- We're building on the methods that have driven extraordinary advances in coding and mathematics, extending them to the harder problems of biology and human health.
- We develop reinforcement learning environments grounded in real scientific data and expert knowledge.
- We've raised a large funding round from leading Silicon Valley investors to achieve this goal.