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# SENIOR MACHINE LEARNING SCIENTIST, FRONTIER RESEARCH LLMS

- **Company:** Genentech
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Computer Programming, Python (Programming Language), Machine Learning, Pytorch, Large Language Models, Deep Learning, Information Technology
- **Published:** November 8, 2026
- **Apply:** https://www.juju.com/job/28_25303_4f721ea75d8a7920434dd29228ce0075

## About the Role

* MS or PhD in Computer Science, Statistics, related field or equivalent experience.
 * 6+ years of industry experience in machine learning.
 * Demonstrated success in technical leadership and in managing teams of machine learning engineers.
 * Experience developing and deploying machine learning models in production environments.
 * Strong programming skills in Python or another relevant language.
 * Experience with deep learning frameworks such as PyTorch.
 * An extensive track record of delivering innovative solutions in machine learning.
 * Strong communication skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiences as well as interfacing with scientific and engineering leadership.
 * Experience collaborating with external scientific partners, such as academic institutions or industry research groups.
 * A passion for solving complex technical problems and a commitment to staying up-to-date with the latest developments in machine learning.

## Description

* Participate in cutting-edge research in machine learning and methods development for scientific discovery, including large language models and drug discovery.
 * Develop and deploy machine learning models in production environments, working closely with other engineers to ensure scalability and reliability.
 * Solve core engineering challenges including the design, implementation, and scaling of our machine learning algorithms.
 * Collaborate closely with cross-functional teams across both Prescient Design and gRED to solve complex problems in the life sciences.