Principal Product Manager, AI Frameworks

Posted 2 Days Ago
Be an Early Applicant
Santa Clara, CA
In-Office
240K-380K Annually
Expert/Leader
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Responsible for building tools, SDKs, and libraries for AI platform training, creating strategies and roadmaps, and collaborating with internal and external customers.
Summary Generated by Built In

At Nvidia we meet customers where they are on their AI journey on our GPUs - this means we build best in class frameworks in OSS and support a robust eco system of other OSS frameworks. and As a Product Manager for AI Platform training you will be responsible for building the tools, SDKs, and libraries which enable model builders to get the best large scale performance, resilience and experience on NVIDIA GPUs.

As NVIDIA Product Managers, our goal is to enable researchers and operators to be successful on the NVIDIA Platform, and push the boundaries of what is possible in their research and research-to-production! As Product Managers, we are the champions inside NVIDIA for frontier model builders looking to push the bounds of scale and resilience for current and emerging modeling paradigms on GPUs. We work directly with customers inside and outside of the company to identify key improvements, create roadmaps, and stay alert on the training/post training landscape. We also work with NVIDIA leaders to define clear product strategy, and marketing team teams to build go-to-market plans. The Product Management organization at NVIDIA is a small, strong, and impactful group. We focus on enabling deep learning across all GPU use cases and providing great products for our users. We are seeking a rare blend of product skills, technical depth, and passion to make NVIDIA great. Does that sounds familiar? If so, we would love to hear from you!

What you'll be doing:

  • Create products to help researchers and production model builders

  • Develop product strategy, roadmaps, and go-to-market plans

  • Collaborate with internal and external customers to build product-based roadmaps for training/post training software

  • Work with leadership to align with and drive company strategy

What we need to see:

  • Experience with training/post training and optimization software (ex. PyTorch distributed, torchtitan, VeRL, Nemo Framework, etc.)

  • Demonstrable knowledge of GenAI or machine learning concepts, particularly around model training, performance optimization, and software development and delivery

  • Experience with large scale distributed systems

  • BS or MS degree in Computer Science, Computer Engineering, or similar experience (or equivalent experience)

  • 15+ years of technical product management, or similar, experience at a technology company

  • Strong communication and interpersonal skills

Ways to Stand Out from the crowd:

  • Experience leading GenAI/RecSys research to production at scale

  • Working on Open Source & Github-first developer products with deep customer interactions

  • Knowledge of GPU architecture, HW/SW co-design, and performance profiling

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 240,000 USD - 379,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 25, 2025.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Top Skills

Gpu
Large Scale Distributed Systems
Machine Learning
Oss Frameworks
PyTorch
Software Development
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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