Role at a glance
- Job function
-
AI & Data AI Research & Applied Science Large Language Model (LLM) Engineering
- Salary
- Not Disclosed
- Location
- San Francisco, United States
- Employment
- Full-time
- Experience
- with up to 2 years of industry research experience (Scientist) or 2+ years of industry research experience (Senior Scientist).
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Role Summary
The Machine Learning Scientist / Senior Machine Learning Scientist will build agentic workflows and machine-learning models for small-molecule drug design. The role develops LLM-driven systems that orchestrate machine-learning models, physics-based methods, and cheminformatics tools in collaboration with chemists and structural biologists.
What You'll Do
- Design, build, and apply agentic workflows and machine-learning models for small-molecule drug-design challenges.
- Fine-tune foundation models for drug-discovery topics using internal and external datasets and tools.
- Optimize agent-derived hypotheses with computational and medicinal chemists and structural biologists.
- Drive scientific impact through publications, open-source releases, and conference talks.
- Collaborate with computational and experimental researchers at Roche and academic partners.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Experience developing LLM-driven agents for scientific workflows; strong machine-learning foundations in linear algebra, probability, and optimization; hands-on experience with GNNs, sequence/language models, and reinforcement learning; fluency in Python, modern agentic coding environments such as LangChain, ML frameworks such as PyTorch or JAX, and cheminformatics toolkits such as RDKit or OpenEye. PhD or equivalent research depth in machine learning, computer science, chemical engineering, or a related quantitative field. Scientific excellence demonstrated by journal and conference publications or a public portfolio of relevant projects.
Required
- Hands-on experience orchestrating multi-tool or multi-agent scientific pipelines.
- Hands-on experience working along the small-molecule drug discovery value chain and excitement to engage with chemists.
- Familiarity with structural biology datasets.
Original job description
Content provided by the employer
Original job description
Content provided by the employer
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.
Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness the transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.
Join the small-molecule team within AI for Drug Discovery (AI4DD), formerly Prescient Design, at Roche and Genentech’s Computational Sciences Center of Excellence as a Machine Learning Scientist / Senior Machine Learning Scientist building agents for applied small-molecule drug design. You will develop autonomous, LLM-driven agentic workflows that orchestrate ML models, physics-based methods, and cheminformatics tools to accelerate discovery, working with world-class chemists and structural biologists.
The Opportunity:
Design, build, and apply agentic workflows and ML models for key challenges in small-molecule drug design.
Fine-tune foundation models for drug discovery relevant topics using internal and external datasets and tools.
Optimize agent-derived hypotheses in close collaboration with world-class computational and medicinal chemists and structural biologists.
Drive scientific impact through publications, open-source releases, and conference talks.
Collaborate widely with computational and experimental researchers at Roche and with academic partners.
Who you are:
You are experienced developing LLM-driven agents for scientific workflows and you understand how to orchestrate tools and models reliably.
You bring strong machine-learning foundations in linear algebra, probability and optimization, with hands-on experience with GNNs, sequence/language models and reinforcement learning.
You are fluent in Python and modern agentic coding environments such as LangChain, ML frameworks such as PyTorch or JAX, as well as cheminformatics toolkits like RDKit or OpenEye.
You hold a PhD or equivalent research depth in machine learning, computer science, chemical engineering or a related quantitative field such as physics or statistics, with up to 2 years of industry research experience (Scientist) or 2+ years of industry research experience (Senior Scientist).
You have a record of scientific excellence evidenced by journal and conference publications or a public portfolio of relevant projects (e.g. hosted on GitHub/GitLab)..
Preferred:
Hands-on experience orchestrating multi-tool or multi-agent scientific pipelines.
Hand-on experience working along the small molecule drug discovery value chain and an excitement to engage with chemists
Familiarity with structural biology datasets
If you want to put autonomous AI to work discovering the medicines patients need next, apply now and help build the future of drug design at Roche.
Relocation benefits are NOT available for this opportunity
The expected salary range for this position, based on the primary location of San Francisco, is $147,600 - $274,000 for the ML Scientist, and $167,400 - 310,800 for the Senior ML Scientist. For the primary of location of New York City, $141.100 - $262,100 for the ML Scientist, and $160,100 - 297,300 for the Senior ML Scientist. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
#ComputationCoE
#tech4lifeComputationalScience
#tech4lifeAI
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.
About the company
Genentech
Large Enterprise
Genentech, a member of the Roche Group, is a biotechnology company focused on discovering, developing, manufacturing, and commercializing innovative medicines for patients with serious medical conditions. Founded in 1976, Genentech has played a pioneering role in the biotech industry, particularly in the development of targeted therapies for cancer and other diseases. The company is committed to advancing science and addressing unmet medical needs through cutting-edge research and collaboration, making it a leader in the field of biotechnology. With a strong emphasis on sustainability and corporate responsibility, Genentech is dedicated to improving patient outcomes and enhancing healthcare globally.