What the work is
Join a leading AI lab's cutting-edge research team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced LLMs.
Overview
Join a leading AI lab's cutting-edge research team and help build foundational AI models for science from the ground up. We're seeking talented Genomics and Cell Biology subject-matter experts (SMEs), including molecular biologists, cell biologists, geneticists and synthetic biologists working at the bench or computationally, to bring recent, hands-on laboratory expertise to the design and evaluation of advanced AI models for biology.
Key Responsibilities
- Guide research and engineering teams to close knowledge gaps and improve AI model performance in molecular cloning, primer and CRISPR design, functional genomics, sequence analysis and cell-based assays.
- Design challenging, non-searchable biology tasks, benchmarks and training data, and write accurate, well-structured solutions to problems such as construct design, protocol planning and assay troubleshooting.
- Evaluate AI model outputs and step-by-step reasoning on biology tasks, judging the biological feasibility of proposed protocols and computational workflows, and provide clear, written technical feedback.
- Develop specifications, grading rubrics and verification processes for biology data produced by external technical teams, and act as the domain authority on data quality.
- Collaborate with other subject matter experts to ensure consistency and accuracy in training data.
Who gets hired
- PhD in molecular biology, cell biology, genetics, genomics, synthetic biology, biochemistry or a closely related discipline. Strong recent PhD graduates and postdoctoral researchers are encouraged to apply.
- Recent, hands-on experience (bench or computational) with workflows such as PCR / qPCR, molecular cloning, CRISPR, cell-based assays, sequence analysis or functional genomics.
- Broad experience across organisms, model systems and methods, rather than a single narrow technique.
- Comfortable using scientific software and AI tools (no coding required).
- Ability to engage reliably for at least 20 hours/week during weekdays.
- Strong written communication and collaboration skills, and the ability to explain complex technical decisions clearly.
- Nice to have: 1 to 3 years of post-PhD experience, or experience evaluating AI models or agents, designing benchmarks, or writing grading rubrics.
The platform posted this on 22 Oct 2026.