ML Scientist I: Generative & Agentic AI for Drug Discovery

RA Cap; South San Francisco (CA); On-site; USD 100,000 - 159,000; Full time

Benefits offered by this job

Health Plan

Retirement Plan

Life Insurance

PTO

Family Leave

Disability

Training & Development

Free Food

Wellness Resources

Stock Options

Job summary

Frontier Medicines is seeking a Machine Learning Scientist to join our AI team in South San Francisco. You’ll build AI systems used by scientists to analyze research data, generate covalent molecules, and predict properties with large datasets.

A research mindset and ability to translate problems into working systems are essential. You’ll collaborate with chemistry and biology teams, with strong Python/PyTorch skills and experience in LLMs, agents, and multimodal models.

Qualifications

• Publications, preprints, thesis work or substantial open-source ML contributions.
• Hands-on experience with LLMs and agents, generative models or multimodal models.
• Strong Python and PyTorch skills, and familiarity with modern AI tooling.

Responsibilities

• Build agentic AI systems for scientific workflows, including multi-agent orchestration, tool calling and MCP integrations.
• Develop and adapt generative models (diffusion, autoregressive transformers, RL-guided generation).
• Build multimodal models and RAG pipelines that reason over molecular data and images.
• Train and benchmark predictive models for property prediction, virtual screening, SAR; include low-data techniques.
• Deploy models and agents so researchers can use them and influence programs.

Skills

LLMs & agents

Generative models

Multimodal models

Python

PyTorch

Independent problem solving

Communication

Education

MS or PhD in CS/ML/comp chemistry/physics or BS + 2-3 yrs exp

Job description

Frontier Medicines is seeking a Machine Learning Scientist to join our AI team in South San Francisco. You’ll build AI systems used by scientists to analyze research data, generate covalent molecules, and predict properties with large datasets.

A research mindset and ability to translate problems into working systems are essential. You’ll collaborate with chemistry and biology teams, with strong Python/PyTorch skills and experience in LLMs, agents, and multimodal models.