Machine Learning (ML) Research Intern – Profluent
Profluent is an AI-first protein design company founded in 2022. Based in Emeryville, CA, the company develops deep generative models to design and validate novel, functional proteins to revolutionize biomedicine. They are backed by leading investors, including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures, and have raised over $150M to date.
Position Summary
The Machine Learning (ML) team at Profluent is seeking a creative and motivated intern to drive research into new technologies for protein design. This position offers an opportunity to leverage advances at the forefront of machine learning for language processing, geometric representation, and proteins. Interns will have broad exposure to the platform’s technologies, including cross-functional interactions with the wet lab and teams regularly deploying new models and algorithms towards specific protein design goals.
Responsibilities
- Research Contribution: Contribute to ML research advancing the state-of-the-art in deep learning for protein sequence, structure, and function and its application to protein design.
- Project Development: Work with a research mentor and the broader ML team to advance a summer research project for peer-reviewed publication or internal deployment.
- Analysis & Reporting: Analyze, interpret, and organize results and present progress to colleagues in regular research meetings.
Qualifications
- Education: Current PhD Student (or equivalent industry experience) in Applied Math, Computer Science, Computational Biology, Machine Learning, Natural Language Processing, Statistics, or a related field.
- Methodology: Experience with conceiving of, implementing, and developing novel machine learning methodology.
- Frameworks: Proficiency with modern deep learning frameworks such as PyTorch or JAX.
Preferences (Not Required)
- Publications at major machine learning conferences (e.g., NeurIPS, ICML, ICLR) or scientific journals (e.g., Nature, Science, Nature Biotech, Nature Methods, PNAS).
- Familiarity with the foundational biology of proteins and nucleic acids.
- Experience developing machine learning models for proteins (language models, structure prediction, design).
What We Offer
- Opportunity to work on "moonshot" projects at the frontier of AI and biology.
- Mentorship from leading experts in bioinformatics, machine learning, and synthetic biology.
- A dynamic, mission-driven environment with the resources of a fast-growing, well-funded startup.
- Competitive internship compensation and benefits.
Profluent Bio, Inc. is an equal opportunity employer promoting diversity and inclusion in the workspace.
