Member of the Technical Staff, Generative

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 biology at scale to discover novel drug treatments and therapies.

Responsibilities

• Lead the design and development of generative models across molecular modalities
• Design architectures and develop training approaches for small molecules, peptides, and mini proteins
• Develop training approaches that learn from diverse biological signals
• Build methods for controllable, targeted generation of molecules with specified properties
• Integrate biological reasoning from foundation models into the generative pipeline
• Own end-to-end training, including experiment design and distributed training on multi-GPU clusters
• Design evaluation frameworks to measure biological meaningfulness and structural validity

Requirements

• PhD in CS, ML, Physics, Math, or related field with 2+ years post-doc/industry experience, or BS/MS with 5+ years experience
• Strong publication record in top-tier venues like NeurIPS, ICML, or ICLR
• Extensive experience designing and training deep generative models
• Proficiency in Python and PyTorch
• Experience training models on distributed multi-GPU infrastructure
• Ability to own the full research-to-training pipeline
• Ability to write production-quality, well-tested, and maintainable code
• Rigorous experimental design and systematic data tracking skills

Preferred Qualifications

• Experience applying generative models to molecular, chemical, or biological data
• Background in chemistry, biology, computational biology, or biophysics
• Experience with multi-modal learning or cross-modality translation
• Experience with conditional or controllable generation methods
• Contributions to open-source machine learning projects