Scientist II / Senior ML Scientist, Cofolding and Structure-Aware ML

Lila Sciences
Cambridge, London, San Francisco
Full timeUSD 228,000 - 358,000 annuallyFunction: Research & Scientific (R&D)Education: phdSkills: ["Collaboration","Experimental design","Evaluation","Scientific reasoning"]

Train and evaluate cofolding models for protein-ligand and structure-aware drug discovery, using contrastive, representation, self-supervised, and multimodal learning. Develop objectives and rigorous evaluation frameworks that separate meaningful molecular learning from artifacts and leakage. Collaborate with ML, computational chemistry and biophysics, data, and research engineering teams to define DEL datasets, labels/negatives/controls, scale workflows, and expose model capabilities for scientist and AI-agent use.

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Lila Sciences
Lila Sciences
3 days ago

Scientist II / Senior ML Scientist, Cofolding and Structure-Aware ML

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Last checked: 21 hours agoStatus: Live

Job Summary

Train and evaluate cofolding models for protein-ligand and structure-aware drug discovery, using contrastive, representation, self-supervised, and multimodal learning. Develop objectives and rigorous evaluation frameworks that separate meaningful molecular learning from artifacts and leakage. Collaborate with ML, computational chemistry and biophysics, data, and research engineering teams to define DEL datasets, labels/negatives/controls, scale workflows, and expose model capabilities for scientist and AI-agent use.
Location: Cambridge, London, San Francisco
Employment Type: Full time
Job Function: Research & Scientific (R&D)
Seniority: Mid level

Key Responsibilities

  • •Train and evaluate cofolding models for protein-ligand and related molecular discovery applications.
  • •Use contrastive, representation, self-supervised, or related methods to improve cofolding models across molecules, proteins, structures, and experimental readouts.
  • •Develop approaches that make DEL data more useful for learning binding, enrichment, selectivity, and structure-activity signals.
  • •Build rigorous evaluation frameworks to detect dataset artifacts, leakage, and spurious correlations.
  • •Collaborate across teams to define datasets and training inputs, scale workflows, and help expose trained models for downstream scientist and AI-agent discovery decisions.

Pay and Benefits

Salary: USD 228,000 - 358,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionLife InsuranceDisability InsurancePaid ParentalEducation Assistance

Key Requirements

  • •PhD or equivalent experience in machine learning, computational biology, computational chemistry, bioinformatics, computer science, or a related field.
  • •Hands-on experience training deep learning models for molecular, protein, structural biology, or scientific data applications.
  • •Experience with contrastive learning, representation learning, self-supervised learning, or multimodal learning.
  • •Familiarity with DEL (or related) selection, enrichment, screening, or molecular assay datasets.
  • •Practical experience with PyTorch, JAX, or an equivalent ML framework.
Education:PhD / Doctorate
Skills:CollaborationExperimental designEvaluationScientific reasoning
Tech Stack:Machine learningPyTorchJAXContrastive learningRepresentation learningSelf-supervised learningMultimodal learningDELBoltzAlphaFoldEquivariant GNNsGeometric deep learningDiffusion modelsProtein language modelsProtein-ligand modelingCofoldingStructure predictionGNNs

Company Brief

Lila Sciences
Develops AI-driven platforms to accelerate drug discovery and biological research by integrating machine learning with chemical and biological data to predict molecular properties, streamline candidate selection, and enable faster therapeutic development.
Industry: Biotech
Company Size: Small (11 to 50 employees)
Growth: Early Stage Startup
Funding: Seed
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