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Scientific Evals
Edison Scientific
San Francisco, USA
Full-time
Mid
Onsite
USD 160000-300000 yearly / year
Discovered 1 weeks ago
Pythondata processingmachine learning
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Pythondata processingmachine learning
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Pythondata processingmachine learning
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About
Edison Scientific builds and commercializes AI agents for science. Scientific discovery moves too slowly, and autonomous AI agents are how we intend to fix that. We're assembling a team of top researchers and engineers across AI and biology to build an AI scientist.
Role
We are seeking an ambitious, scientifically grounded person to join our team focused on developing rigorous benchmarks and training datasets that advance AI capabilities in biology. This role sits at the intersection of biology, data curation, and machine learning, and is ideal for someone with deep scientific training who is excited to shape how frontier AI systems learn to do science. This role is on-site at our San Francisco office in the Dogpatch neighborhood. Our office is a converted warehouse with high ceilings, open space, and a team that genuinely believes in what they're building.
This position is part of the Evals team.
Responsibilities
- Design benchmarks that capture the complexity of real biological research, drawing on your domain expertise to identify what makes scientific reasoning hard. This will include open-ended scientific benchmarks and building on prior work like LAB-Bench and BixBench.
- Curate and vet biological datasets to ensure scientific rigor.
- Analyze model outputs, identify failure modes, and contribute to iterative improvements in both datasets and evaluation criteria.
- Collaborate with AI/ML researchers to translate scientific intuition into training signal, helping AI systems learn not just facts but how scientists think.
- Coordinate operations and manage workflows, including working with domain experts, tracking task progress, and maintaining documentation.
Qualifications
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