Principal Machine Learning Engineer, Infrastructure (LLM)

$188,200 - $349,400/Yr

Genentech - New York, NY

Full-time - Senior

New York, NY

Chemical Manufacturing

About the position

The Principal Machine Learning Engineer, Infrastructure (LLM) at Genentech Computational Sciences (gCS) Prescient Design will play a pivotal role in advancing drug discovery through machine learning. This position focuses on designing, constructing, and optimizing large-scale distributed systems, particularly for machine learning infrastructure. The engineer will contribute to cutting-edge research, develop innovative algorithms, and support the deployment and scalability of compute-intensive large language models (LLMs) and AI systems, essential for scientific discovery.

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 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.

Nice-to-haves

• 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 available
• Discretionary annual bonus based on individual and company performance