Agentic Life Science Expert, Computational AI

You will turn real life sciences research methods into challenging workflows that AI agents can complete in a controlled, network-isolated environment. The work tests scientific reasoning and practical execution, not simple question answering.

This listing uses the title Agentic Life Science Expert. Review the duties and qualifications below before applying to make sure they match your background.

• Design multi-step scientific workflows across the life sciences.
• Create realistic input files, datasets, instructions, constraints, and expected deliverables.
• Write reproducible expert solutions and objectively verifiable ground truths.
• Create automated or semi-automated grading criteria for agent performance.
• Build tasks involving data inspection, method selection, code execution, troubleshooting, and result synthesis.
• Check scientific assumptions, calculations, code, intermediate outputs, and final answers.
• Keep each task self-contained and executable in a provided sandbox.
• Respond to reviewer feedback and maintain task quality.

This is a remote contractor assignment lasting five weeks. The role is marked for entry-level experience, while the listed work requires advanced research and programming skills.

• Pay: $280 per approved task.
• Location: Remote and open worldwide.
• Schedule: At least 40 hours per week, including at least six hours per day and four hours overlapping with Pacific Time.
• Experience level: Entry level.
• Education and experience: Ph.D., postdoctoral training, or equivalent research experience in the life sciences.
• Programming: Strong scientific programming experience, especially in Python.
• Analysis: Experience with multi-step computational scientific analyses and validating computational outputs.
• Task design: Ability to turn authentic research workflows into bounded, objectively gradable tasks.
• Tools: Familiarity with scientific libraries, command-line tools, or reproducible research pipelines.
• Language: Fluent in English.
• Helpful backgrounds include bioinformatics, computational genomics, systems biology, computational neuroscience, biostatistics, computational drug discovery, computational biochemistry, structural biology, protein engineering, and computational microbiology.

Apply on OpenTrain with your resume, then complete the application on the hiring site.

AI training is the human work behind systems that learn from examples and feedback. In this role, your scientific expertise helps create reliable tasks for evaluating how AI agents reason, use tools, write code, and produce valid results.