Genentech
Senior Machine Learning Engineer, Prescient LLMs
Genentech, San Francisco, California, United States, 94199
The Position
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 Genentech, a member of the Roche Group.The Opportunity
At Genentech Computational Sciences (gCS) Prescient Design, we are revolutionizing drug discovery with ground breaking machine learning techniques. We are seeking talented engineers with a passion for building large-scale machine learning algorithms and systems that will transform the drug discovery process.gCS Prescient Design is seeking an exceptional Senior Machine Learning Engineer to develop our LLM and AI product and enable the next generation of foundational research in machine learning for scientific discovery. We are looking for someone who is not only passionate about technical problem-solving but also has a consistent record of delivering innovative solutions in machine learning. The ideal candidate should have extensive experience in developing, serving, and maintaining models and APIs , and be able to foster a culture of innovation, collaboration, and excellence across the broader gCS organization.The group provides a dynamic and challenging environment for multidisciplinary research including access to heterogeneous data sources, close links to top academic institutions around the world, as well as collaborations with internal Genentech and Roche teams.In this role, you will:
Participate in cutting-edge development of large language models for drug discovery and scientific applications.Develop and deploy machine learning models, especially LLMs, in production environments, working closely with other engineers to ensure scalability and reliability.Solve core research 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.Who you are
QualificationsMS or PhD in Computer Science, Statistics, related field or equivalent experience.4+ years of industry experience in machine learning.Experience developing and deploying LLMs in production environments.Strong programming skills in Python or another relevant language.Experience with deep learning frameworks such as PyTorch.Extensive understanding of general machine learning as well as LLMs.An extensive track record of delivering and serving innovative solutions in machine learning.PreferredStrong 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.
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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 Genentech, a member of the Roche Group.The Opportunity
At Genentech Computational Sciences (gCS) Prescient Design, we are revolutionizing drug discovery with ground breaking machine learning techniques. We are seeking talented engineers with a passion for building large-scale machine learning algorithms and systems that will transform the drug discovery process.gCS Prescient Design is seeking an exceptional Senior Machine Learning Engineer to develop our LLM and AI product and enable the next generation of foundational research in machine learning for scientific discovery. We are looking for someone who is not only passionate about technical problem-solving but also has a consistent record of delivering innovative solutions in machine learning. The ideal candidate should have extensive experience in developing, serving, and maintaining models and APIs , and be able to foster a culture of innovation, collaboration, and excellence across the broader gCS organization.The group provides a dynamic and challenging environment for multidisciplinary research including access to heterogeneous data sources, close links to top academic institutions around the world, as well as collaborations with internal Genentech and Roche teams.In this role, you will:
Participate in cutting-edge development of large language models for drug discovery and scientific applications.Develop and deploy machine learning models, especially LLMs, in production environments, working closely with other engineers to ensure scalability and reliability.Solve core research 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.Who you are
QualificationsMS or PhD in Computer Science, Statistics, related field or equivalent experience.4+ years of industry experience in machine learning.Experience developing and deploying LLMs in production environments.Strong programming skills in Python or another relevant language.Experience with deep learning frameworks such as PyTorch.Extensive understanding of general machine learning as well as LLMs.An extensive track record of delivering and serving innovative solutions in machine learning.PreferredStrong 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.
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