Job Description
The role: • Extend and scale Diffuse's in-house deep generative modeling toolkit for downstream applications in molecular design. • Thoughtfully execute deep learning experiments to improve performance of models or develop new functionality (e.g. loop engineering, structure prediction of protein-protein complexes). • Work closely with software engineers to build systems for efficient training and deployment of deep learning models. Ideal background: • Self-starter who enjoys working on tough scientific problems and is results-driven.
• Able to think critically, methodically, and creatively about experiments. • Proficient in Python. • Experience working with deep learning frameworks (e.g., PyTorch). • 3+ years of industry experience in a data science or engineering position. • Track record of impressive work in industry/academia centered on ML / deep learning. • Graduate degree in math, CS, stats, bioengineering, comp bio, or a related field (not a hard requirement for exceptional candidates). • Is located in the Bay Area (remote work is an option for exceptional candidates).
Pluses: • Knowledge of physics, math, molecular biology, chemistry, etc. • Previous work on ML applied to problems in structural biology or molecular design. • Strong publication record. What we offer: • The opportunity to join the founding team and play a critical and expanding role in shaping the company. • The opportunity to work on cutting-edge AI with leading researchers from top institutions. Apply tot his job