Genentech - South San Francisco, CA

posted about 1 month ago

Full-time - Senior
South San Francisco, CA
Chemical Manufacturing

About the position

The Principal Machine Learning Engineer, Infrastructure (LLM) at Genentech will play a pivotal role in advancing drug discovery through the development of machine learning infrastructure. This position focuses on designing, constructing, and optimizing large-scale distributed systems, particularly for large language models (LLMs) and AI systems. The engineer will contribute to cutting-edge research, develop innovative algorithms, and collaborate with cross-functional teams to solve complex problems in life sciences.

Responsibilities

  • Contribute to cutting-edge research in machine learning, including algorithm and method development for drug discovery and large language models (LLMs).
  • Develop and maintain robust tools for large-scale ML experiments, focusing on deployment, optimization, and scalability of compute-intensive LLM training.
  • Tackle engineering challenges involving the design, implementation, and scaling of dynamic, distributed, and high-performance machine learning systems.
  • Engage in collaboration with cross-functional teams to solve complex problems in life sciences, leveraging language models for scientific applications.

Requirements

  • MS or PhD in Computer Science, Statistics, Machine Learning, or related field, or equivalent experience.
  • 6+ years of industry experience relating to distributed systems and machine learning.
  • Proven expertise in designing and implementing large-scale machine learning models and infrastructure.
  • Demonstrated success in technical leadership for teams of engineers.
  • Practical hands-on experience with PyTorch in a production environment.
  • Excellent programming skills.
  • Familiarity with large language models (LLMs) and their training is highly desirable.
  • A keen interest in molecular design and a desire to contribute to scientific and computational advancements.

Benefits

  • Relocation benefits are available for this opportunity.
  • Discretionary annual bonus based on individual and Company performance.
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