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Posted 6 hours ago
Member of the Technical Staff, Interpretability
OutputMember of the Technical Staff, Interpretability
Perks & benefits
Health InsuranceMedical InsuranceVisa
Requirements
PhD in CS, ML, Physics, or Math with 2+ years experience, Strong publication record (NeurIPS, ICML, ICLR), Proficiency in Python and PyTorch, Experience with large-scale GPU infrastructure, Experience in mechanistic interpretability
Skills
PythonPyTorchMachine Learning
About the role
About the Company
Output is a stealth-mode startup operated by repeat founders and biotech veterans. The company is building biological reasoning models that understand molecular interactions to generate novel therapies, backed by top-tier VCs including Y Combinator.
Responsibilities
- Develop methods for probing and reverse-engineering model representations to understand biological encoding
- Design and run experiments to identify and characterize model capabilities regarding molecular interactions
- Build methods to extract biological understanding as explicit, usable outputs for downstream systems
- Create tools connecting model internals to meaningful biological concepts for scientists
- Collaborate with pretraining and generation teams to feed interpretability findings back into model development
- Own the full pipeline from probing experiments to production-quality interpretability tools on distributed infrastructure
Requirements
- PhD in CS, ML, Physics, Math, or related field with 2+ years post-doc/industry experience, OR Bachelor's/Master's with 5+ years research/engineering experience
- Strong publication record at top-tier venues (NeurIPS, ICML, ICLR) in mechanistic interpretability or representation analysis
- Hands-on experience analyzing internal representations of large neural networks
- Proficiency in Python and PyTorch
- Experience working with large models on GPU infrastructure
- Ability to write production-quality, well-tested, and maintainable code
- Experience taking research from experiments to usable tools
Preferred Qualifications
- Background in chemistry, biology, computational biology, or biophysics
- Experience interpreting ML models trained on scientific or biological data
- Experience building visualization or analysis tools for model internals
- Experience with multimodal models
- Contributions to open-source machine learning projects
Benefits
- Competitive salary and equity
- Medical, dental, and vision coverage
- Feedback-focused environment with high autonomy
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Output · New York
