Senior ML Scientist: Cofolding & Structure-Aware ML

Lila Sciences; San Francisco, Cambridge (CA, MA); On-site; USD 228,000 - 358,000; Full time

Job summary

Lila Sciences in San Francisco, CA is seeking a Scientist II / Senior ML Scientist to advance cofolding and structure-aware ML for drug discovery. You will train models that reason over proteins, ligands, context, and experimental readouts, potentially using contrastive learning and related representation-learning approaches.

You will collaborate with ML researchers, computational chemists, biophysicists, and data engineers to connect model outputs to chemically meaningful hypotheses, design

Qualifications

• PhD or equivalent in ML, computational biology, computational chemistry, bioinformatics, CS or related field.
• Hands-on experience training deep learning models for molecular, protein, structural biology, or scientific data applications.
• Experience with contrastive, representation, self-supervised, or multimodal learning.
• Familiarity with DEL or related selection, enrichment, screening, or molecular assay datasets.
• Experience with protein-ligand modeling, cofolding, structure prediction, or geometric deep learning.
• Proficiency with PyTorch, JAX, or equivalent ML framework.
• Ability to design careful experiments, ablations, and evaluations for scientific ML models.
• Strong understanding of data quality, leakage risks, negative construction, and benchmark design.

Responsibilities

• Train and evaluate cofolding models for protein–ligand and related molecular discovery applications.
• Use contrastive learning, representation learning, self-supervised learning, or multimodal objectives to improve models.
• Develop training objectives that connect ligands, proteins, structures, assays, and experimental data.
• Build rigorous evaluation frameworks that distinguish meaningful molecular learning from dataset artifacts.
• Collaborate with data and platform teams to define datasets, labels, negatives, controls, and metadata.

Skills

PhD/MLE experience

Hands-on DL in molecular data

Contrastive/representation/self-superv

Protein-ligand modeling

PyTorch/JAX

Experiment design & benchmarking

Education

PhD or equivalent in ML/related

Tools

PyTorch

JAX

Diffusion models

Geometric DL

Job description

Lila Sciences in San Francisco, CA is seeking a Scientist II / Senior ML Scientist to advance cofolding and structure-aware ML for drug discovery. You will train models that reason over proteins, ligands, context, and experimental readouts, potentially using contrastive learning and related representation-learning approaches.

You will collaborate with ML researchers, computational chemists, biophysicists, and data engineers to connect model outputs to chemically meaningful hypotheses, design