Machine Learning Scientist I - Generative & Agentic AI for Drug Discovery
South San Francisco, CAJob$100–159K/yrSeen todaySeen in employer's feed today
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At a glance
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Job overview
Frontier Medicines seeks a Machine Learning Scientist to build AI systems for scientific workflows, including LLM-powered agents, generative models for covalent molecules, and predictive models using proprietary chemistry and chemoproteomics data. The scientist will work with medicinal chemistry, biology, and computational chemistry teams. Drug discovery experience is not required; the company says it will teach the chemistry.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
Frontier Medicines is looking for a Machine Learning Scientist to join our AI team in South San Francisco. You’ll build the AI systems our scientists use every day: LLM-powered agents that work across our research data, generative models that design new covalent molecules, and predictive models trained on one of the largest proprietary covalent chemistry and chemoproteomics datasets in the industry.
This role suits someone with a research mindset who wants their work to reach real decisions. You’ll work in a small team with short communication lines to medicinal chemistry, biology, and computational chemistry. Prior drug discovery experience is not required. If you bring strong AI fundamentals and curiosity, we’ll teach you the chemistry.
Requirements
What you’ll do
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Build agentic AI systems for scientific workflows, including multi-agent orchestration, tool calling and MCP integrations, task decomposition, and human-in-the-loop checkpoints. These systems connect to our scientific databases and compound registry.
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Develop and adapt generative models (diffusion, autoregressive transformers, RL-guided generation) to explore new covalent chemical space.
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Build multimodal models and RAG pipelines that reason over molecular structures, assay data, protein structures, slide decks, reports, and images.
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Train and benchmark predictive models for property prediction, virtual screening, and SAR. This includes approaches for low-data settings such as transfer, multi-task, and active learning.
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Deploy models and agents so researchers can use them, and see your work influence active programs.
What we’re looking for
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MS or PhD in computer science, machine learning, computational chemistry, physics, or a related field, or a BS with 2–3 years of equivalent industry or research experience.
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A track record of research: publications, preprints, thesis work, or substantial open-source contributions in ML.
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Hands-on experience building with LLMs and agents, generative models, or multimodal models.
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Strong Python and PyTorch skills, and comfort with modern AI coding tools.
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The ability to take an open-ended scientific problem and turn it into a working system, independently and collaboratively.
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Clear written and verbal communication.
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Legal authorization to work in the United States.
Nice to have
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Experience with molecular ML, such as GNNs, equivariant models, or molecular representations, or with RDKit and cheminformatics tooling.
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Experience with large-scale or distributed training (DeepSpeed, FSDP, MoE).
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Exposure to biology, chemistry, or drug discovery data.
Benefits
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Health Care Plan (Medical, Dental & Vision)
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Retirement Plan (401k, IRA)
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Life Insurance (Basic, Voluntary & AD&D)
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Paid Time Off (Vacation, Sick & Public Holidays)
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Family Leave (Maternity, Paternity)
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Short Term & Long Term Disability
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Training & Development
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Free Food & Snacks
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Wellness Resources
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Stock Option Plan
At Frontier, we strive to build a diverse and equitable workplace. The salary range for this role is $100,000 - $158,900. Compensation for the role will depend on a number of factors, including candidates' qualifications, skills, competencies and experience. Frontier offers a competitive total rewards package which includes healthcare coverage, 401k and a broad range of other benefits.
This compensation and benefits information is based on Frontier's knowledge as of the date of publication, and may be modified in the future.
How this job compares
Set against the 518 open Machine Learning Scientist jobs on Olive Jobs, counted November 12, 2026.
- Pay
- This posting$100–159K/yr
- California median$176–260K/yr121 salary ranges
- US median$143–235K/yr470 salary ranges
This range's midpoint, $129K, is 41% below the California median midpoint ($218K) — in the lowest quarter of Machine Learning Scientist salary ranges in California.
- Openings
- Olive Jobs lists 131 open Machine Learning Scientist jobs in California and 518 across the US. 6% of them nationwide are listed as remote or flexible.
- Experience
- Machine Learning Scientist postings that state a minimum ask for 3 years of experience at the median; the middle half ask for 3 to 6 years (427 postings).
- Education
- 115 of the 518 open Machine Learning Scientist jobs (22%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 12, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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