Senior ML Engineer - Structure Modeling for Life Science AI

Lilasciences; San Francisco (CA); On-site; USD 252,000 - 374,000; Full time

Job summary

Lila Sciences is hiring a Senior/Principal ML Engineer to lead end-to-end development of structure prediction and co-folding models. You will own problem formulation, architecture, training at scale, evaluation, and integration into Lila's Lab-in-the-Loop discovery engine.

We seek a leader who can drive research on AlphaFold-style methods, protein language models, and geometry-based ML, collaborating with wet-lab and computational biologists to translate complex questions into robust ML

Qualifications

• PhD in a quantitative field and ability to lead research programs end-to-end.
• Experience formulating and driving research from problem to deployment.
• Fluency in ML with life sciences domain and cross-disciplinary collaboration.

Responsibilities

• Lead research on structure prediction and co-folding models for protein complexes.
• Design, train, and evaluate models at scale using large GPU clusters.
• Set evaluation standards and ensure generalization to de novo design problems.
• Shape end-to-end ML processes within the Lab-in-the-Loop lifecycle and data strategy.
• Represent the work in publications and at premier venues.

Skills

PhD required

Independent research leadership

ML + life science domain

Cross-functional collaboration

ML frameworks + distributed training

Education

PhD in CS/ML/Computational Biology/Biophysics

Tools

PyTorch

JAX

TensorFlow

AWS

GCP

Job description

Lila Sciences is hiring a Senior/Principal ML Engineer to lead end-to-end development of structure prediction and co-folding models. You will own problem formulation, architecture, training at scale, evaluation, and integration into Lila's Lab-in-the-Loop discovery engine.

We seek a leader who can drive research on AlphaFold-style methods, protein language models, and geometry-based ML, collaborating with wet-lab and computational biologists to translate complex questions into robust ML