Diffuse Bio
Generative AI for protein design
What Diffuse Bio does
Diffuse is building generative AI for protein design. Our mission is to build AI systems that engineer new and useful proteins with unprecedented control and accuracy. Our team has been behind breakthroughs in AI protein design for the past 7 years, including the first experimental validation of AI-generated proteins and diffusion models for protein structure and sequence.
2 open roles
What the role involves
The role: Design, build, and iterate on research infrastructure in close collaboration with research engineers. Build tools to automate and maintain computing clusters and data parsing pipelines. Design and build software and APIs that enable internal and external access to our AI systems. Ideal background: Adaptability and openness to work on multiple problem areas (e.g. data processing pipelines, front-end software development). Fast learner with a broad understanding of infrastructure, front-end, databases, CI, etc. Bachelors or Graduate Degree in Computer Science, or a related field (not a hard requirement for an exceptional candidate). Strong track record in programming (industry experience, internships, competitions, open-source projects). Proficient in Python and C++. Experience with cloud computing platforms (e.g., GCP). Data science or engineering experience (e.g. ML engineer, data infrastructure engineer). Is located in the Bay Area (remote work is an option for exceptional candidates). Pluses: Experience with Kubernetes or other cluster management platforms. Front-end experience and proficient in HTML/CSS/Javascript, React, etc. 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 with an application and productization focus.
What the role involves
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.
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Company facts compiled from public sources and last refreshed 9 September 2026. Details change; treat the company’s own site as the authority.