Remote Biochemist: AI Data Trainer

Alignerr; New York (NY); Remote; USD 55,000 - 83,000; Part time

Benefits offered by this job

Fully remote

Flexible hours

Freelance autonomy

Global collaboration

Exposure to AI model training

Job summary

Alignerr is seeking a PhD-level biochemist to stress-test AI reasoning on topics like protein folding and metabolic pathways. This fully remote hourly contract role asks for domain expertise without requiring prior AI experience, with 10–40 hours per week.

Design complex biochemistry challenges, author rigorous solutions, and audit AI outputs to improve model accuracy and safety. Join a remote, freelance-friendly team shaping scientific AI models.

Qualifications

• PhD (completed or in final stages) in Biochemistry, Molecular Biology, or closely related discipline.
• Strong foundational knowledge in structural biology, enzymology, cellular metabolism, bioinformatics, or molecular genetics.
• Analytical writer able to clearly communicate complex biological concepts in writing.
• Detail-oriented with high precision reviewing data and protocols.
• No prior AI or ML experience required.

Responsibilities

• Design Advanced Problems across biochemistry domains to probe AI performance.
• Author gold-standard, step-by-step solutions for high-level reasoning.
• Audit AI outputs for technical accuracy and safety.
• Refine AI reasoning by documenting errors and providing structured feedback.

Skills

Analytical writing

Detail-oriented

Domain expertise

Molecular genetics

Enzymology

Education

PhD in Biochemistry or Molecular Biology

Tools

PyMOL

AlphaFold

BLAST

Job description

Alignerr is seeking a PhD-level biochemist to stress-test AI reasoning on topics like protein folding and metabolic pathways. This fully remote hourly contract role asks for domain expertise without requiring prior AI experience, with 10–40 hours per week.

Design complex biochemistry challenges, author rigorous solutions, and audit AI outputs to improve model accuracy and safety. Join a remote, freelance-friendly team shaping scientific AI models.