Lila Sciences

3 months ago

Senior / Principal ML Scientist, Foundation Models for Life Sciences

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Lead and shape foundation model research at the intersection of machine learning and life sciences. Define problem statements, design and train large-scale generative models, collaborate with wet-lab scientists, publish in premier venues, and drive end-to-end ML workloads from data strategy to deployment within Lila's discovery engine.

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Drive research on foundation models for life science applications, including but not limited to biological sequence design, structure prediction, and multimodal scientific reasoning.
•Design, train, and evaluate large-scale generative models on biological and chemical data, integrating domain-specific constraints and priors.
•Contribute to the end-to-end ML process within Lila's Lab-in-the-Loop lifecycle: steer data generation strategy, build pipeline models, and design feedback loops where experimental results improve model performance.
•Translate complex biological questions into well-defined ML problems and interpret model outputs in collaboration with wet-lab scientists and computational biologists.
•Represent Lila's foundation model research externally through publications at premier venues, conference presentations, and community engagement.

Pay and Benefits

Salary: USD 288,000 - 480,000 annually

Perks:Health InsuranceDentalVisionLife InsuranceCommuter BenefitsMeal AllowanceRemote Work

Key Requirements

•PhD in Computer Science, Machine Learning, Computational Biology, or a related quantitative field.
•Multiple high-impact first-author or senior-author publications at premier venues (NeurIPS, ICML, ICLR, Nature Methods, Nature Biotechnology, or equivalent).
•Deep expertise in large-scale generative model architectures and training, with hands-on experience training models on distributed infrastructure.
•Demonstrated ability to formulate and drive research programs independently, from problem definition through publication and deployment.
•Fluency across ML and at least one life science domain (molecular biology, genomics, protein engineering, nucleic acid design, or related), with experience designing computational experiments grounded in biological reality.

Experience:Life sciencesAiMachine learningBiotech

Education:PhD / Doctorate

Skills:PyTorchJAXTensorFlowDistributed trainingBiologyMolecular biologyGenomicsProtein engineeringNucleic acid design

Languages:English

Tech Stack:PyTorchJAXTensorFlowAWSGCPOn-premDistributed training

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

Website LinkedIn

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Lila Sciences

3 months ago

Senior / Principal ML Scientist, Foundation Models for Life Sciences

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Drive research on foundation models for life science applications, including but not limited to biological sequence design, structure prediction, and multimodal scientific reasoning.
•Design, train, and evaluate large-scale generative models on biological and chemical data, integrating domain-specific constraints and priors.
•Contribute to the end-to-end ML process within Lila's Lab-in-the-Loop lifecycle: steer data generation strategy, build pipeline models, and design feedback loops where experimental results improve model performance.
•Translate complex biological questions into well-defined ML problems and interpret model outputs in collaboration with wet-lab scientists and computational biologists.
•Represent Lila's foundation model research externally through publications at premier venues, conference presentations, and community engagement.

Pay and Benefits

Salary: USD 288,000 - 480,000 annually

Perks:Health InsuranceDentalVisionLife InsuranceCommuter BenefitsMeal AllowanceRemote Work

Key Requirements

•PhD in Computer Science, Machine Learning, Computational Biology, or a related quantitative field.
•Multiple high-impact first-author or senior-author publications at premier venues (NeurIPS, ICML, ICLR, Nature Methods, Nature Biotechnology, or equivalent).
•Deep expertise in large-scale generative model architectures and training, with hands-on experience training models on distributed infrastructure.
•Demonstrated ability to formulate and drive research programs independently, from problem definition through publication and deployment.
•Fluency across ML and at least one life science domain (molecular biology, genomics, protein engineering, nucleic acid design, or related), with experience designing computational experiments grounded in biological reality.

Experience:Life sciencesAiMachine learningBiotech

Education:PhD / Doctorate

Skills:PyTorchJAXTensorFlowDistributed trainingBiologyMolecular biologyGenomicsProtein engineeringNucleic acid design

Languages:English

Tech Stack:PyTorchJAXTensorFlowAWSGCPOn-premDistributed training

Company Brief

Lila Sciences

Industry: Biotech

Company Size: Small (11 to 50 employees)

Growth: Early Stage Startup

Funding: Seed

Website LinkedIn