Senior Machine Learning Researcher for Chemistry

3 weeks ago


South San Francisco, California, United States Genentech Full time
Job Summary

We are seeking a highly motivated Machine Learning Scientist to join our team at Genentech Computational Sciences (gCS) Prescient Design. The successful candidate will collaborate extensively with computational and experimental scientists and researchers across gRED to deploy and deliver machine-learning solutions for small-molecule drug discovery.

About the Role

This is an exciting opportunity to work on creating novel LLM applications that interface directly with medicinal chemistry and molecular design processes. You will focus on enhancing predictions of biochemical properties, chemical reactivity, and synthesizability. By collaborating extensively with computational and experimental scientists across gRED, you will develop, deploy, and deliver innovative machine-learning solutions that significantly advance our small-molecule drug discovery pipeline.

Responsibilities

- Fine tune modern LLM architectures and implement agentic workflows for applications in computational chemistry and small molecule drug discovery
- Design, build, and maintain robust and scalable ML pipelines and workflows that integrate machine learning solutions with internal and external cheminformatics and computational chemistry tools and APIs
- Spearhead the creation and curation of high-quality, diverse datasets that fuel cutting-edge ML models, directly impacting the success of drug discovery projects
- Contribute to and drive publications, present results at internal and external scientific conferences, and help make code and workflows open source

Requirements

- BS/MS with - 5 years of experience or recent PhD in the physical sciences (e.g., Chemistry, Physics, Chemical Engineering) or quantitative field (e.g., Computer Science, Statistics, Applied Mathematics) or equivalent industry research experience
- Experience working with medicinal chemistry or chemical reaction datasets and familiarity with chemistry, cheminformatics, and small molecule drug discovery concepts
- Experience with toolkits for chemical modeling (e.g., RDKit, OpenEye Toolkits)
- Fluency in Python and demonstrated experience with modern Python frameworks for deep learning (e.g., PyTorch, Hugging Face Transformers)
- Experience with cloud platforms (e.g., AWS, GCP, Azure), version control systems (e.g., Git), and CI/CD pipelines

Preferred

- Strong experience in scientific software development and ML engineering, including fine-tuning modern LLM architectures and building ML pipelines

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