AI Summary
Design graduate-level computational problems using domain-specific scientific software libraries. Collaborate with teams to improve AI model performance. Requires graduate-level STEM training and proficiency in scientific software libraries like scikit-rf or ngspice.
Key Highlights
Design computational problems using domain-specific scientific software libraries
Collaborate with teams to improve AI model performance
Work independently and iterate on problem designs based on feedback
Key Responsibilities
Design graduate-level computational problems using domain-specific scientific software libraries
Develop problems requiring sophisticated use of scikit-rf for RF and microwave network analysis and ngspice for circuit simulation
Calibrate tasks against state-of-the-art AI models and refine designs to achieve target difficulty
Create problems that demand strategic reasoning to uncover hidden information from data
Work independently and iterate on problem designs based on calibration feedback
Collaborate asynchronously with teams to improve AI model performance
Technical Skills Required
Benefits & Perks
Compensation: $70–$100/hour
Location: Remote
Commitment: 15–20 hours/week
Job Description
About The Job
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.
Position: STEM Computational Scientific Software & Evaluation Design - Electrical Engineering & RF/Circuit Design
Type: Contract
Compensation: $70–$100/hour
Location: Remote
Commitment: 15–20 hours/week
Role Responsibilities
- Design graduate-level computational problems using domain-specific scientific software libraries.
- Develop problems requiring sophisticated use of scikit-rf for RF and microwave network analysis and ngspice for circuit simulation.
- Calibrate tasks against state-of-the-art AI models and refine designs to achieve target difficulty.
- Create problems that demand strategic reasoning to uncover hidden information from data.
- Work independently and iterate on problem designs based on calibration feedback.
- Collaborate asynchronously with teams to improve AI model performance.
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Must-Have
- Graduate-level training in a relevant STEM domain (MS, PhD, or equivalent research experience).
- Demonstrated proficiency with scientific software libraries like scikit-rf or ngspice.
- Strong Python programming 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.
- 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.
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- Upload resume
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- Submit form
- 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: [email protected]
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