ML Scientist I/II: AI-Driven Protein Design (Equity)

Lila Sciences; San Francisco (CA); On-site; USD 176,000 - 304,000; Full time

Job summary

Lila Sciences is seeking an ML Scientist I/II focused on AI for protein engineering. You will build ML workflows across design, evaluation, and experimental learning, collaborating with ML researchers, biologists, and platform teams to accelerate design and discovery of biologics.

The role requires a PhD in a quantitative field and hands-on experience applying ML to protein design, with strong collaboration and communication skills across disciplines.

Qualifications

• PhD in a quantitative field as listed.
• Experience applying ML to protein design or related biomolecular problems.
• Strong ML fundamentals with hands-on model development and evaluation.
• Ability to translate therapeutic or biological objectives into computational design problems.

Responsibilities

• Build ML workflows for protein engineering campaigns, from design specification through experimental learning.
• Develop methods spanning de novo generation, sequence- or structure-based property prediction, candidate selection, and active learning.
• Integrate protein design methods into robust software systems and broader reasoning models.
• Translate therapeutic and biological questions into well-defined ML problems, model outputs, and evaluation plans.
• Partner with experimental scientists to interpret why designed biomolecules succeed or fail, then improve models.
• Build evaluation frameworks for model generalization to challenging biologics design problems.

Skills

ML fundamentals

Cross-functional collaboration

Protein engineering basics

Model evaluation experience

Education

PhD in Computational Biology, Computer Science, Machine Learning, Biophysics, Bioengineering, or related field

Job description

Lila Sciences is seeking an ML Scientist I/II focused on AI for protein engineering. You will build ML workflows across design, evaluation, and experimental learning, collaborating with ML researchers, biologists, and platform teams to accelerate design and discovery of biologics.

The role requires a PhD in a quantitative field and hands-on experience applying ML to protein design, with strong collaboration and communication skills across disciplines.