Computational Life Sciences AI Task Designer

OpenTrain AI, Inc.; United States; Remote; USD 55,000 - 96,000; Part time

Benefits offered by this job

Remote work

Part-time contract

Worldwide access

Job summary

OpenTrain AI, Inc. is seeking a part-time, remote contractor to design self-contained scientific workflows that test AI agents on realistic computational research tasks. The role focuses on scientific reasoning, code execution, troubleshooting, and producing valid deliverables, not simple Q&A.

You will craft data, instructions, constraints, expected results, and grading methods to enable objective evaluation of workflows in the life sciences, with emphasis on Python and multi-step analyses.

Qualifications

• Ph.D. or equivalent life sciences research experience.
• Strong Python programming and scientific computation skills.
• Experience designing and validating multi-step scientific analyses.

Responsibilities

• Design self-contained workflows to evaluate AI agents on realistic computational research tasks.
• Create datasets, instructions, constraints, expected results, and grading criteria.
• Develop reproducible pipelines and objective ground truths for evaluation.

Skills

Python

Scientific programming

Multi-step analyses

Life sciences

Education

Ph.D. in Life Sciences

Postdoctoral experience

Tools

Docker

Linux

Job description

The work

You will design self-contained scientific workflows that test whether AI agents can carry out realistic computational research. The work focuses on scientific reasoning, code execution, troubleshooting, and valid research deliverables rather than simple question answering.

Tasks run in controlled, reproducible, network-isolated environments. You will create the data, instructions, constraints, expected results, and grading methods needed to evaluate each workflow objectively.

• Design challenging computational workflows across the life sciences.
• Create realistic input files, scientific datasets, instructions, constraints, and expected deliverables.
• Develop reproducible expert solutions and objectively verifiable ground truths.
• Build automated or semi-automated grading criteria for multi-step analyses.
• Validate scientific assumptions, calculations, code, intermediate outputs, and final answers.
• Package dependencies, data, and computational resources so tasks run reliably.
• Maintain quality and throughput while using reviewer feedback.

What it pays and takes

This is a remote, part-time contract role for an individual contributor. The listing does not state a pay rate.

• Pay: Not specified in the listing.
• Time: 20+ hours per week.
• Location: Worldwide and remote.
• Language: English.
• Work type: Contractor and part-time.
• Experience level: Listed as entry level, with a requirement for a Ph.D., postdoctoral work, or equivalent life sciences research experience.
• Required skills: Strong scientific programming experience, especially in Python, and experience with multi-step computational scientific analyses.
• You must be able to validate scientific reasoning and computational outputs independently and create bounded, reproducible, objectively gradable research workflows.

Helpful background

Relevant experience includes bioinformatics, computational genomics, systems biology, computational neuroscience, biostatistics, computational drug discovery, computational biochemistry, structural biology, protein engineering, and computational microbiology.

• Scientific libraries and command-line tools.
• Reproducible research pipelines and computational life sciences publications.
• AI agents, coding agents, or automated evaluation environments.
• Docker, Linux, and domain-specific scientific software.

About AI training work

AI training is the human work behind systems that learn from examples, including scientific tasks, code, and model evaluations. People with specialized experience help check whether AI produces accurate, useful work in complex fields such as the life sciences.