Computational Biologist - Fully Remote | Upto $100/hr

mercor; Deutschland; Remote; EUR 86,000 - 123,000; Part time

Job summary

Mercor is seeking a highly capable problem-set designer for AI evaluation tasks. You will craft challenging computational problems using domain-specific scientific libraries, focusing on reproducibility and scalable workflows.

This remote, part-time role fits around 15–20 hours per week and requires strong STEM background and Python proficiency. You will collaborate with AI research teams to calibrate tasks against cutting-edge models, iterate designs from feedback, and ensure high-quality

Qualifications

• Graduate-level training in a relevant STEM field (MS/PhD or equivalent).
• Proficiency with at least one listed scientific software library.
• Strong Python programming skills for problem setups and validators.
• Ability to work independently in a remote environment.
• Familiarity with Linux/terminal and remote compute sandboxes.

Responsibilities

• Design challenging computational problems using domain-specific scientific software libraries like libRoadRunner, Tellurium, or 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 problem design to achieve target difficulty.
• Collaborate with AI research teams to improve model outputs and training data quality.
• Work independently and asynchronously to meet deadlines and improve AI model performance.

Skills

Python programming

Linux/terminal

Independent work

Scientific software libraries

Education

MS/PhD or equivalent

Tools

libRoadRunner

Tellurium

SBML-based tools

Job description

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 .

Type: Contract Compensation: $70-$100/hour Location: Remote Commitment: 15-20 hours/week

Role Responsibilities

• Design challenging computational problems using domain-specific scientific software libraries like libRoadRunner , Tellurium , or 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 problem design to achieve target difficulty.
• Collaborate with AI research teams to improve model outputs and training data quality.
• Work independently and asynchronously to meet deadlines and improve AI model performance.

Qualifications

Must-Have

• 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 research publications, open-source contributions, or professional work.
• Strong Python programming skills for writing 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.

Preferred

• 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.