Machine Learning Infrastructure Lead

2 days ago


South San Francisco, California, United States Genentech Full time
About the Role

We're looking for a Machine Learning Infrastructure Lead to join our team at Genentech Computational Sciences. As a key member of our Prescient Design group, you'll play a leading role in developing and maintaining large-scale machine learning models and infrastructure.

About the Responsibilities

This role involves:

  • Contributing to cutting-edge research in machine learning, including algorithm and method development, specifically applicable to drug discovery and large language models.
  • Architecting, developing, and maintaining robust tools for large-scale ML experiments, focusing on the deployment, optimization, and scalability of compute-intensive LLM training and lab-in-the-loop molecular design.
  • Tackling complex engineering challenges that involve the design, implementation, and scaling of dynamic, distributed, and high-performance machine learning systems such as models deployed as APIs, retrieval augmented generation (RAG) systems, search and advanced generative models of text, images, and structures, such as molecules.
About the Requirements

To succeed in this role, you should have:

  • A MS or PhD in Computer Science, Statistics, Machine Learning, or a related field, or equivalent experience.
  • 10+ 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 and mentorship 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.
About the Benefits

We offer a comprehensive benefits package, including relocation benefits, a discretionary annual bonus, and access to a range of perks and programs designed to support your well-being and career growth.



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