Product Manager, Core Machine Learning

$168,000 - $252,000/Yr

Google - Sunnyvale, CA

Full-time - Mid Level

Sunnyvale, CA

Web Search Portals, Libraries, Archives, and Other Information Services

About the position

The Product Manager for Core Machine Learning at Google will lead the development and execution of machine learning software products, focusing on Open Accelerated Linear Algebra (XLA) and its integration with major ML hardware partners. This role requires collaboration across various teams to drive product development from conception to launch, ensuring that products meet user needs and leverage cutting-edge technology.

Responsibilities

• Drive improvements to Google's OpenXLA core developer experience, including Stable High-Level Operations (HLO) and PJRT, release quality, test and release, and community management.
• Enhance OpenXLA's Hardware Engineer (HW) partner evaluation and adoption through sustained engagements with executive technical leaders.
• Drive the development of improved XLA tooling, including monitoring, profiling, and debugging, for both internal and external use cases.
• Analyze PyTorch's compilation stack, including its strengths and weaknesses, and position and advocate OpenXLA as an alternative.

Requirements

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in product management or related technical role.
• 5 years of experience developing ML software or infrastructure.
• Experience interfacing externally and with senior product/technical leadership at the Director level and above.

Nice-to-haves

• Master's degree in a technology or a business related field.
• Experience prototyping and building Generative Artificial Intelligence (genAI) products or applications.
• Experience with the PyTorch SW stack - Dynamo, Inductor, Triton, and associated NVIDIA libraries (cuBLASS, cuDNN, CUTLASS).

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• 401(k) plan
• Paid holidays
• Paid time off
• Employee stock purchase plan
• Tuition reimbursement
• Professional development opportunities
• Flexible scheduling