Related skills
python pytorch gpu interpretability representation_analysis📋 Description
- Probe and reverse-engineer the model's representations across molecular scales.
- Design experiments to map model capabilities and biological function.
- Build methods to extract the model's biological understanding as usable outputs.
- Create tools linking internals to biological concepts for interpretation.
- Collaborate with pretraining and generation teams to feed findings back into development.
- Own end-to-end pipeline from probing to production-grade interpretability tools.
🎯 Requirements
- PhD in CS/ML/physics/math with 2+ years postdoc/industry research in interpretability; or BA/MA with 5+ years.
- Strong publication record at top venues on mechanistic interpretability or probing.
- Hands-on experience analyzing internal representations of large neural networks and designing experiments.
- Proficient in Python and PyTorch; experience with large models on GPU.
- Ability to translate interpretability research into usable tools and production-grade code.
- Production-quality, well-tested code; comfortable with version control and code reviews.
- Bonus: chemistry/biology background; ML on scientific data; visualization tools.
🎁 Benefits
- We encourage new ideas, creativity and contrarian thinking.
- Healthy feedback-focused environment with constructive feedback.
- You own your day-to-day management; aim for milestones.
- Competitive salary and equity in a growing startup.
- Excellent medical, dental, and vision coverage.
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