ML Scientist, Protein Design & Autonomous Discovery

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

Benefits offered by this job

Medical, dental, and vision coverage

Commuter benefits

Company subsidized lunch program

Educational assistance program

Bike share memberships

Job summary

Lila Sciences is seeking a machine learning scientist to design molecules on real programs and turn learnings into capabilities that generalize across projects. You will work with domain scientists, platform teams, and AI researchers to connect design models to the autonomous science platform.

Ideal candidates are exceptional builders with strong biological intuition, able to turn experiments into scalable systems that improve molecule design across programs. This role is based in the U.S.

Qualifications

• MS or PhD in computer science, ML, computational biology, biophysics, bioengineering, or related field.
• Strong software engineering and system design fundamentals.
• Rigor in evaluation and dataset design; understanding benchmarks and validation.
• Strong cross-functional communication skills.
• Domain expertise in protein sequence, structure, and function.

Responsibilities

• Design molecules for active biologics programs in collaboration with domain scientists.
• Develop reasoning capabilities for drug discovery and coordinate design workflows.
• Design and maintain benchmarks and evaluation infrastructure for decisions across biologics programs.
• Own operations around reproducibility, throughput, and inference cost of computational design workflows.
• Translate domain scientist priorities into ML objectives and evaluation criteria.

Skills

Cross-functional communication

Biology-domain intuition

Software engineering fundamentals

Evaluation and dataset design

Education

MS or PhD in computer science, ML, computational biology, biophysics, bioengineering, or equivalent

Job description

Lila Sciences is seeking a machine learning scientist to design molecules on real programs and turn learnings into capabilities that generalize across projects. You will work with domain scientists, platform teams, and AI researchers to connect design models to the autonomous science platform.

Ideal candidates are exceptional builders with strong biological intuition, able to turn experiments into scalable systems that improve molecule design across programs. This role is based in the U.S.