Bioinformatics AI Evaluation Task Designer

OpenTrain AI, Inc.; United States; Remote; USD 3,000 - 5,000; Full time

Benefits offered by this job

Remote work worldwide

Job summary

OpenTrain AI, Inc. is seeking a remote contractor to design and evaluate challenging computational genomics tasks over a five-week period. You will create datasets, reference solutions, and automated grading for AI evaluation, using Python and standard bioinformatics tools.

The role requires a Ph.D. or equivalent experience in bioinformatics or genomics, strong Python skills, and comfort with Linux. Expected overlap with Pacific Time and remote worldwide work arrangement.

Qualifications

• Ph.D., postdoc or equivalent research experience in bioinformatics or genomics.
• Strong hands-on Python programming.
• Experience with biological sequence or genomics datasets.
• Comfort with Linux and command-line environments.
• Education or experience: Ph.D., postdoc or equivalent.

Responsibilities

• Design novel tasks using FASTA, FASTQ, VCF, BAM, SAM, BED, TSV, and CSV files.
• Work with sequence annotations, expression data, and germline or somatic variant data.
• Create task specifications, input datasets, expected outputs, and reference solutions.
• Build reproducible workflows with Python, Linux CLI, and bioinformatics libraries.
• Check scientific correctness, solvability, reproducibility, and difficulty.
• Create grading criteria that separate correct from plausible incorrect results.
• Document deliverables and communicate requirements to project leads and reviewers.

Skills

Python

Bioinformatics

Linux

Education

Ph.D.

Postdoctoral experience

Tools

Biopython

Pandas

NumPy

SciPy

Samtools

Bcftools

BLAST

PLINK

Job description

The Work

You will create challenging computational genomics and bioinformatics problems for advanced AI evaluation. Each task should require an AI system to interpret biological data, write and run code, use scientific file formats, and produce outputs that can be checked objectively.

The role combines scientific judgment, computational analysis, benchmark design, reference-solution development, and detailed quality review.

• Design novel tasks using FASTA, FASTQ, VCF, BAM, SAM, BED, TSV, and CSV files.
• Work with sequence annotations, expression data, and germline or somatic variant data.
• Create task specifications, input datasets, expected output schemas, deterministic ground truths, and expert reference solutions.
• Build reproducible workflows with Python, Linux command-line tools, and established bioinformatics libraries.
• Check scientific correctness, solvability, reproducibility, and difficulty.
• Create grading criteria that separate scientifically correct answers from plausible-looking but incorrect results.
• Document deliverables and communicate technical requirements, blockers, and progress to project leads and reviewers.

What It Pays and Takes

This is a remote contractor assignment lasting five weeks. The work requires strong scientific and programming experience in bioinformatics or a closely related field.

• Pay: $150 per approved task.
• Time: At least 20 hours per week.
• Schedule: Include a four-hour overlap with Pacific Time.
• Location: Remote and open worldwide.
• Education or experience: Ph.D., postdoctoral experience, or equivalent research experience in bioinformatics, computational biology, genomics, computational genetics, or a related discipline.
• Required skills: Strong hands-on Python programming, experience with biological sequence or genomics datasets, and comfort with Linux and command-line environments.
• Scientific knowledge: Understand the experimental and biological context behind computational analyses.
• Helpful experience: Variant analysis, transcriptomics, sequence analysis, phylogenetics, population genetics, functional genomics, or clinical genomics.
• Helpful tools: Biopython, pandas, NumPy, SciPy, samtools, bcftools, BLAST, PLINK, or equivalent tools.
• Also useful: AI or language model evaluation, benchmark or automated grader design, reproducible pipelines, Docker, or containerized scientific workflows.
• Benefits: The assignment does not include medical or paid leave.

About AI Training Work

AI training work uses examples, evaluations, and human feedback to help artificial intelligence systems produce better results. In specialist projects like this one, researchers and technical experts help ensure that scientific tasks, reference answers, and grading rules are accurate.