Lila Sciences

4 weeks ago

Co-Op, ML Scientist for Protein Engineering

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Join the Life Science AI team at Lila Sciences as an ML Scientist Co-Op focused on protein engineering, antibody design, and related biomolecule design problems. Contribute to generative and predictive modeling for protein sequence/structure, collaborate with scientists to translate design goals into computational tasks, analyze experimental data, and prototype workflows that integrate model predictions with wet-lab feedback.

Location: San Francisco

Workplace: Onsite

Employment Type: Internship

Job Function: Research & Scientific (R&D)

Seniority: Intern level

Key Responsibilities

•Contribute to ML research projects focused on protein engineering, antibody design, and related biomolecule design problems.
•Explore generative and predictive modeling approaches for protein sequence, structure, function, and developability.
•Work with scientists and ML researchers to translate biological design goals into tractable computational problems.
•Analyze biological and experimental datasets to identify patterns, evaluate model outputs, and guide design decisions.
•Prototype workflows that connect model predictions, candidate prioritization, and wet-lab feedback.

Key Requirements

•Currently enrolled as a PhD student in Computer Science, Machine Learning, Computational Biology, Bioengineering, Biophysics, or a related quantitative field.
•Research experience in machine learning, computational biology, protein engineering, or a closely related area.
•Strong programming skills in Python and experience with modern ML frameworks such as PyTorch, JAX, or similar tools.
•Ability to work with biological sequence, structure, assay, or other scientific datasets.
•Interest in applying ML methods to real biological design problems in partnership with experimental scientists.

Experience:Machine learningComputational biologyProtein engineeringBiomedical AIBiophysics

Skills:CommunicationCollaborationTeamworkProblem-solving

Languages:English

Tech Stack:PythonPyTorchJAX

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

4 weeks ago

Co-Op, ML Scientist for Protein Engineering

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Onsite

Employment Type: Internship

Job Function: Research & Scientific (R&D)

Seniority: Intern level

Key Responsibilities

•Contribute to ML research projects focused on protein engineering, antibody design, and related biomolecule design problems.
•Explore generative and predictive modeling approaches for protein sequence, structure, function, and developability.
•Work with scientists and ML researchers to translate biological design goals into tractable computational problems.
•Analyze biological and experimental datasets to identify patterns, evaluate model outputs, and guide design decisions.
•Prototype workflows that connect model predictions, candidate prioritization, and wet-lab feedback.

Key Requirements

•Currently enrolled as a PhD student in Computer Science, Machine Learning, Computational Biology, Bioengineering, Biophysics, or a related quantitative field.
•Research experience in machine learning, computational biology, protein engineering, or a closely related area.
•Strong programming skills in Python and experience with modern ML frameworks such as PyTorch, JAX, or similar tools.
•Ability to work with biological sequence, structure, assay, or other scientific datasets.
•Interest in applying ML methods to real biological design problems in partnership with experimental scientists.

Experience:Machine learningComputational biologyProtein engineeringBiomedical AIBiophysics

Skills:CommunicationCollaborationTeamworkProblem-solving

Languages:English

Tech Stack:PythonPyTorchJAX

Company Brief

Lila Sciences

Industry: Biotech

Company Size: Small (11 to 50 employees)

Growth: Early Stage Startup

Funding: Seed

Website LinkedIn