ML Scientist I/II, AI for Protein Engineering

Highlights

• Build generative models that move protein designs from hypothesis to wet-lab leads.
• Partner with wet-lab teams to turn design results into improved models.
• Build evaluation frameworks for challenging biologics design problems.

What they offer

• Bonus potential
• Early-stage equity
• Medical, dental and vision coverage
• Employer-paid life and disability insurance
• Flexible time off with company holidays
• Paid parental leave
• Educational assistance program
• Commuter benefits and subsidized lunch

Ideal candidate

ML scientist with strong fundamentals and curiosity for protein biology who enjoys turning therapeutic questions into models and learning from wet-lab results with experimental collaborators.

Requirements

• PhD in Computational Biology, Computer Science, Machine Learning, Biophysics, Bioengineering, or related quantitative field
• Experience applying machine learning to protein design, biologics engineering, or related biomolecular design problems
• Strong ML fundamentals with hands-on experience developing, adapting, training, or evaluating modern AI methods
• Fluency with biological sequence, structure, function, developability, or experimental validation considerations
• Ability to translate therapeutic or biological objectives into computational design problems and evaluation plans
• Strong collaboration and communication skills across ML, biology, experimental science, and software teams