ML Scientist I/II, AI for Protein Engineering

What you'll do

• Build protein engineering ML workflows, including design, candidate selection, and experimental learning.
• Develop methods for protein generation, property prediction, and active learning; integrate them into software and reasoning systems.
• Collaborate with experimental scientists to evaluate designs and improve models and generalization.

What they ask for

• PhD in Computational Biology, Computer Science, Machine Learning, Biophysics, Bioengineering, or a related quantitative field.
• Experience applying machine learning to protein design, biologics engineering, or related biomolecular design problems.
• Strong ML fundamentals and hands-on experience developing, adapting, training, or evaluating modern AI methods.
• Fluency with biological sequence, structure, function, developability, or experimental validation considerations.

Nice to have

• Experience designing antibodies, nanobodies, enzymes, peptides, or other therapeutic proteins.
• Experience with structure prediction, generative protein design, diffusion models, flow matching, or protein language models.

Pay

$176,000 — $304,000 USD (base salary)

Tools

ML, AI, diffusion models, flow matching, protein language models

AI focus

Generative and predictive AI for protein engineering, including de novo generation, property prediction, candidate selection, active learning, and model evaluation.