Senior ML Scientist, AI for Protein Engineering

What you'll do

• Lead applied ML workflows for protein-engineering campaigns, from design specification to experimental learning.
• Develop and integrate generative, predictive, candidate-selection, and active-learning methods into software and reasoning systems.
• Collaborate with experimental scientists to evaluate design outcomes and improve models and design principles.

What they ask for

• PhD in a related quantitative field, including Computational Biology, Computer Science, Machine Learning, Biophysics, or Bioengineering.
• Strong track record applying machine learning to protein design, biologics engineering, or related biomolecular design problems.
• Hands-on expertise adapting and developing modern AI methods.
• Ability to drive applied research independently from problem definition through experimental validation and iteration.

Nice to have

• Industry experience in the relevant area.
• Experience with therapeutic protein design, generative protein design, structure prediction, diffusion models, flow matching, protein language models, or wet-lab design-test-learn loops.

Pay

$268,000 — $358,000 USD (base salary)

Tools

machine learning, generative and predictive models, active learning, diffusion models, flow matching, protein language models

AI focus

Develops generative and predictive AI for protein engineering, including candidate selection, evaluation, and active learning, with experimental feedback to improve biomolecule design.