Computational Biologist

Stack

Responsibilities

• ▹Design challenging computational problems using domain-specific scientific software libraries (e.g. libRoadRunner, Tellurium, SBML-based tools)
• ▹Develop problems that test AI systems' ability to implement complex multi-step scientific workflows and strategic reasoning
• ▹Calibrate tasks against state-of-the-art AI models, refining difficulty
• ▹Collaborate with AI research teams to improve model outputs and training data quality
• ▹Work independently and asynchronously to meet deadlines and improve model performance

Requirements

• ▹Graduate-level training in a relevant STEM domain (MS, PhD, or equivalent research experience)
• ▹Proficiency with at least one listed scientific software library, evidenced by publications, open-source contributions, or professional work
• ▹Strong Python programming skills for problem setups, oracle functions, and solution validators
• ▹Ability to work independently and iterate on problem designs based on calibration feedback
• ▹Comfortable in a Linux/terminal environment with remote compute sandboxes

Nice to have

• ▹Experience across multiple listed domains or tools
• ▹Familiarity with benchmark or evaluation design
• ▹Background in scientific pedagogy or exam/problem-set design
• ▹Experience with computational reproducibility and containerized environments

About the company

Mercor connects elite creative and technical talent with leading AI research labs; headquartered in San Francisco, with investors including Benchmark, General Catalyst, and Peter Thiel.