Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.
- Design challenging computational problems to evaluate AI capabilities in solving scientific tasks.
- Develop problems requiring the use of specialized scientific software like scikit-rf and ngspice.
- Test and refine problems against state-of-the-art AI models to achieve target difficulty.
- Collaborate with research teams to improve AI model performance and training data quality.
- Work independently and asynchronously to meet deadlines and refine problem designs.
Qualifications
Must-Have
- Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience).
- Proven proficiency with scientific software libraries like scikit-rf or ngspice.
- Strong Python skills for writing problem setups and solution validators.
- Ability to work in a Linux/terminal environment with remote compute sandboxes.
- Available for at least 15–20 hours per week.
Preferred
- Experience across multiple listed domains or tools.
- Familiarity with benchmark or evaluation design.
- Background in scientific teaching or exam/problem-set design.
- Experience with computational reproducibility and containerized environments.
Application Process (Takes 20–30 mins to complete)
- Upload resume
- AI interview based on your resume
- Submit form
Resources & Support
- For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
- For any help or support, reach out to:
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this chance.