Computational Genomics AI Task Designer

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. OpenTrain AI is recruiting contributors for specialized projects where expert judgment helps shape how advanced AI systems perform.

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About AI Training and Scientific Evaluation

AI training is the human side of building artificial intelligence. Experts create examples, evaluate model outputs, and design benchmarks that help AI systems solve real problems more accurately and reliably.

In this role, your computational genomics expertise will help turn authentic bioinformatics workflows into tasks that AI agents must solve with code, scientific files, and defensible reasoning.

The Computational Genomics AI Task Designer Role

OpenTrain is seeking a Computational Genomics AI Task Designer to create realistic scientific problems and expert reference solutions for AI agents. You will design challenging, objectively verifiable benchmark tasks involving biological data, computational analysis, and scientifically defensible outputs.

This is a remote contractor assignment for an individual freelancer. The engagement lasts six weeks and requires 40 hours per week, including four hours of overlap with Pacific Standard Time. The structured opportunity is listed for contributors available for 20 or more hours per week.

• Engagement: Six-week contractor assignment
• Work arrangement: Remote
• Commitment: 40 hours per week
• Time-zone overlap: Four hours with Pacific Standard Time
• Listed availability: 20+ hours per week
• Language: English
• Experience level listed: Entry level, with advanced computational genomics expertise required

What You'll Do

You will translate real computational genomics and bioinformatics workflows into reproducible AI evaluation tasks. The work combines scientific judgment, Python programming, dataset design, reference-solution development, and objective grading.

You will also examine ambiguous or messy data, identify artifacts, test assumptions, and determine whether analytical conclusions are ready to support a decision.

• Design model-challenging tasks in computational genomics and bioinformatics.
• Work with FASTA, FASTQ, VCF, BAM, SAM, BED, TSV, and CSV files.
• Use sequence annotations, expression data, and germline or somatic variant data.
• Create task specifications, input datasets, expected output schemas, and ground truths.
• Develop reproducible Python reference solutions using scientific libraries and bioinformatics tools.
• Design grading criteria that separate scientifically correct answers from superficially plausible outputs.
• Document deliverables, incorporate reviewer feedback, and communicate technical or scientific blockers.

Required Qualifications

This role requires advanced computational genomics and bioinformatics judgment. A Ph.D., postdoctoral experience, or equivalent research experience in bioinformatics, computational biology, genomics, computational genetics, or a closely related discipline is required.

You should have substantial hands-on Python experience for scientific analysis, experience working with biological sequence or genomics datasets, and comfort using Linux and command-line computational environments.

• Ph.D., postdoctoral experience, or equivalent research experience in a relevant discipline.
• Hands-on Python programming for scientific analysis.
• Experience analyzing sequence, variant, or expression datasets.
• Proficiency with Linux and command-line workflows.
• Ability to design reproducible benchmark tasks and reference solutions.
• Ability to create objective grading criteria for scientific outputs.

Helpful Experience

The following background is useful for designing realistic and demanding scientific benchmarks. These qualifications are valuable additions to the required experience.

• Variant analysis, transcriptomics, sequence analysis, or phylogenetics.
• Population genetics, functional genomics, or clinical genomics.
• Biopython, pandas, NumPy, SciPy, samtools, bcftools, BLAST, or PLINK.
• Reproducible scientific pipelines and benchmark datasets.
• AI or large language model evaluation and automated graders.
• Docker or containerized scientific workflows.

Who Should Apply

This opportunity is suited to a computational biologist, bioinformatician, geneticist, or related researcher who can combine scientific reasoning with practical software development. It is especially relevant if you enjoy converting complex analyses into clear, testable tasks and evaluating whether an AI-generated solution is genuinely correct.

The role is available to candidates located in the countries below. English is the listed working language.

• Bangladesh
• Brazil
• Colombia
• Egypt
• Ghana
• India
• Pakistan
• Indonesia
• Kenya
• Nigeria
• Turkey
• Vietnam

How to Apply Through OpenTrain

OpenTrain helps people start and grow careers in AI training and data labeling, including specialized work that draws on advanced scientific expertise. Create a free OpenTrain account, build a profile that reflects your computational genomics background, and apply to this contractor assignment in minutes.

Your work will contribute to the human evaluation layer behind modern AI systems, helping make scientific reasoning and computational analysis more reliable.

• Create a free OpenTrain account.
• Highlight your genomics, bioinformatics, Python, and Linux experience.
• Review the engagement requirements and location eligibility.
• Apply through OpenTrain.