Biology Expert – Applied Biology Benchmark Specialist
Compensation
$75 – $75 /hr
Employment type
Full-time
Work setting
On-site
Location
San Francisco, CA
Schedule
Day shift
Posted
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Job overview
The Biology Expert – Applied Biology Benchmark Specialist role is remote, with a commitment of at least 10 hours per week. Compensation is $60–$75 per hour. Mercor connects technical talent with AI research labs. The specialist creates and reviews biology assessment questions and solutions for AI benchmarking. The work contributes subject-matter expertise to evaluating conceptual understanding across applied biology domains.
What you'll do
- Author original biology questions covering pharmaceutical manufacturing, industrial and synthetic biology, medical research and drug discovery, and agricultural, environmental, and food biology
- ensure questions are clear and self-contained
- rate difficulty and provide one correct answer with nine plausible alternatives
- write step-by-step solutions in markdown
- provide academic references
- review verification tasks for clarity, completeness, precision, and solvability.
What we're looking for
- Skills & competencies
- biology expertapplied biology benchmark specialistremotemercorbiologyai researchquestion authoringpharmaceutical manufacturingsynthetic biologydrug discovery$60–$75/hr
- Work arrangement
- Weekend coverage required
Why this role
The posting describes a contract engagement and requires a PhD or doctoral candidacy in a relevant biological field; a master’s degree may be considered for exceptional depth in a subdomain. Research publications or laboratory experience are preferred.
About the employer
Mercor is hiring for this role. Industry: Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology). Sector: 54.
Additional details
- Industry sector
- 54
- Industry
- Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)
- Occupation code
- 19-1029.00
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Listing ID: b7fa6163-52be-4cf3-b02b-d2a10089eb92