Senior Scientist – AI Protein Design & Foundation Models (3709)

A biotechnology company operating in the protein space is seeking a Senior AI Protein Design Scientist with deep expertise in AI and machine learning, specifically applied to protein design.

This role is focused explicitly on AI-driven approaches — including training, adapting, and deploying AI models and foundation models for protein design — and will serve as the professional lead for this domain.

This is a hands-on, senior scientific role, combining technical depth in AI with scientific leadership and close collaboration with protein engineering teams.

Key Responsibilities

• Lead the AI Protein Design domain, with a clear focus on machine learning and foundation models
• Design, train, fine-tune, and evaluate AI/ML models for protein sequence and structure design
• Own the end-to-end AI workflow: data curation, model architecture, training, validation, and iteration
• Translate high-level company and scientific goals into practical AI-driven protein design roadmaps
• Develop and maintain scalable computational pipelines for AI-based protein design
• Collaborate closely with experimental and computational protein scientists to support design–build–test cycles
• Stay up to date with advances in foundation models, generative models, and deep learning for proteins
• Evaluate and integrate external tools, models, and frameworks where appropriate
• Independently execute complex AI protein design tasks while providing scientific leadership and direction

Requirements

• PhD in Computational Biology, Bioinformatics, Machine Learning, Biophysics, Computer Science, or a related field
• Proven hands-on experience in AI-based protein design – mandatory
• Strong experience in training and adapting machine learning models, including deep learning architectures
• Demonstrated work with foundation models and generative models for proteins, such as:
• Protein language models (e.g., ESM, ProtBERT, ProGen)
• Diffusion-based protein design models
• ProteinMPNN or similar sequence-generation models
• Practical experience with protein structure prediction and modeling tools (e.g., AlphaFold, Rosetta) as part of AI workflows
• Strong programming skills in Python; experience with PyTorch and/or TensorFlow – required
• Experience working with large biological datasets and high-performance or cloud computing environments – advantage
• Ability to independently lead AI-driven scientific initiatives from concept to execution
• Industry experience – advantage; strong PhD/Postdoc experience with applied focus is also welcome
• Excellent communication skills and ability to work across AI and protein science teams

Why Join

• Clear ownership of the AI layer within a strong protein science organization
• Opportunity to shape how foundation models and AI drive real protein design outcomes
• High-impact, hands-on role at the intersection of AI and biology
• Collaborative environment combining experimental, computational, and AI expertise