About Diffuse Bio

Generative AI for protein design

Tech description:

We’re building cutting edge models and software for generative molecular design, and our primary focus is innovating on the algorithms and approaches. We’re also building a seamless software product to deploy our models internally and to external customers/partners and back-end solutions to enable rapid model inference and distributed training.

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.

Skills:

Python, Deep Learning, Machine learning

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