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Biochemistry & Life Sciences Domain Expert

$105
per hour
Full-time Hybrid Last verified 21 Jul 2026
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About the Role

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced AI models. We are hiring a senior biochemistry and life sciences domain expert to work directly with a leading AI lab's research and program management teams, improving how frontier AI models reason about real life sciences research work. Your scientific expertise is the substance of this role. You will review the quality of life sciences knowledge work tasks, write the instruction specs and golden solutions that define what "correct" looks like, and build the benchmarks that show whether the model is genuinely improving. We are looking for a practicing specialist rather than a generalist.

What You'll Do

  • Data QA and reviews: Vet the quality of life sciences knowledge work tasks and model outputs, spotting missing behaviors, thin reasoning, mechanistic hand-waving, unsupported causal claims, and answers that read well but would not survive peer review.
  • Instruction specs and golden datasets: Write high-quality instruction specs, produce golden solutions to life sciences problems, and define new tasks that reflect how the research is actually done in practice.
  • Benchmarks and domain depth: Design challenging life sciences tasks and evaluation sets, and help build domain-specific skills and tools together with the research team.
  • Calibration: Work with client researchers and specialists in adjacent fields to keep standards consistent, translating tacit scientific judgment into explicit, teachable criteria.

You're a Good Fit If You

  • Education: PhD in biochemistry, molecular or cell biology, genetics, immunology, neuroscience, or a closely related life science.
  • Experience: 4+ years of substantive research experience at a recognized institution, for example a research university, an academic medical center, a national laboratory, or an industrial research organization. Graduate coursework alone does not count.
  • Domain depth: Genuine specialization in at least one area, for example molecular and cell biology, biochemistry and structural biology, immunology and immuno-oncology, genetics and genomics, neuroscience, or systems biology.
  • Seniority: Clear progression to a senior level, for example Senior Scientist, Staff Scientist, Research Scientist, Instructor, Principal Investigator, or a faculty appointment, with real ownership of research direction.
  • Research record: A record of peer-reviewed publications, ideally including first-author work in strong journals. Strongly preferred.
  • AI fluency: Hands-on working use of large language models in your professional work, and the judgment to tell a well-reasoned answer from a plausible-sounding wrong one.
  • Availability: Able to commit reliably to 40 hours per week for an initial engagement of 6 months.
  • Location: Living in the Bay Area, California, and able to work on-site with the client's team multiple days each week, when required. Candidates not currently based in the Bay Area must be willing to relocate there at their own cost. Relocation assistance is not provided.

Role Highlights

Pay
$65-$105/h
Contract
Full-time
Location
Hybrid
Category
Research
Posted
2 months ago
Job ID
WE-7868

Pay & Payout

Independent contractor engagement. Apply via the link below - Mercor handles onboarding and pays weekly via Stripe or Wise.

Common Questions

Mercor has a reliability rating of very reliable based on the listings we track, with an onboarding time of 1-3 weeks (interview + assessment + trial). See our full Mercor review for the details behind that rating.

Applying takes you to Mercor's own website, where the application is completed. We are not a recruiter or employer and do not process applications directly - we may be recorded as the referring source.

$65-$105/h - Independent contractor engagement. Apply via the link below - Mercor handles onboarding and pays weekly via Stripe or Wise.

Data QA and reviews: Vet the quality of life sciences knowledge work tasks and model outputs, spotting missing behaviors, thin reasoning, mechanistic hand-waving, unsupported causal claims, and answers that read well but would not survive peer review. Instruction specs and golden datasets: Write high-quality instruction specs, produce golden solutions to life sciences problems, and define new tasks that reflect how the research is actually done in practice. Benchmarks and domain depth: Design challenging life sciences tasks and evaluation sets, and help build domain-specific skills and tools together with the research team.

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