What You'll Be Building- Agentic AI for science: Systems that perform sequential decision-making and multi-step reasoning to solve domain-specific problems.
- Workflow/code generation: From natural language intent to typed, executable steps for lab instruments.
- Evaluation & reliability: Benchmarks, test suites, and telemetry to measure capability and quantify progress toward scientific goals.
What You'll Need to Succeed- PhD or Masters in a quantitative discipline (e.g., Computer Science, Physics, Mathematics, Engineering) with a strong background in machine learning and one domain of science (e.g. biology or materials science).
- Strong grasp of LLMs and agent architectures (planning, tool use, structured function calling, code generation) and how to adapt them to domains.
- Proficiency in modern ML frameworks (e.g., PyTorch, TensorFlow, JAX) and experience implementing scalable solutions for complex tasks.
- Comfort collaborating across disciplines and interfacing with simulations and real lab systems.
Bonus Points For - Building long-horizon agents or RL for control/decision-making; experience with model-based or offline RL.
- Designing domain-specific benchmarks and evaluation harnesses for complex scientific tasks.
- Digital-twin development, calibration, and sim-to-real transfer.
- Publications or open-source contributions in AI for science (especially publications in top-tier conferences like NeurIPS, ICML, AAAI, ICLR).
LocationSan Francisco, CA or Cambridge, MA (Hybrid and On-Site available depending on team needs).
CompensationWe offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.
International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Expected Base Salary Range
$148,000-$240,000 USD
