Principal Product Manager, AI Frameworks

The NVIDIA PyTorch Compilers team builds and upstreams to the stack that sits between PyTorch and NVIDIA hardware, spanning torch.compile, emerging compiler substrates, and the agent-native optimization infrastructure for the next era of accelerated computing. This role will own the strategy for NVIDIA's PyTorch compiler portfolio, including:

• torch.compile — maintain and evolve NVIDIA's upstream PyTorch path, drive HW support, resolve customer issues across dynamic shapes, kernel performance, and compile overhead
• define the roadmap and go-to-market for NVIDIA's shared representation layer across frameworks, compilers, kernel libraries, and runtimes
• agent-native compiler workflows — shape the product vision for how agentic systems will participate in optimization tasks
• inter-kernel optimization features — build product requirements for capabilities like megakernels and ensure they ship with demonstrated real-world value

What You'll Be Doing

• Own the strategy for NVIDIA's PyTorch compiler portfolio, including:
• torch.compile — maintain and evolve NVIDIA's upstream PyTorch path, drive HW support, resolve customer issues across dynamic shapes, kernel performance, and compile overhead
• define the roadmap and go-to-market for NVIDIA's shared representation layer across frameworks, compilers, kernel libraries, and runtimes
• agent-native compiler workflows — shape the product vision for how agentic systems will participate in optimization tasks
• inter-kernel optimization features — build product requirements for capabilities like megakernels and ensure they ship with demonstrated real-world value

Lead Product Strategy Across The Roadmap

• Define Now/Next/Later priorities in close partnership with engineering leads
• Translate ecosystem signals (vLLM RFCs, SGLang CUDA Graph patterns, TorchTitan GraphTrainer plans, Meta's upstream priorities) into prioritized product decisions
• Engage directly with customers and partners
• Represent NVIDIA at PyTorch contributor and ecosystem forums
• Define success metrics and release criteria
• Set performance gates and adoption milestones
• Set bar for what "proven" means for new optimizations before committing to roadmap

What We Need To See

• 15+ years in technical product management, with 5 years owning a compiler, runtime, or low-level systems product at scale
• BS or MS degree in Computer Science, Electrical Engineering, a related technical field, or equivalent experience
• Experience with OSS-first products and upstream contribution strategy
• Track record of shipping and driving adoption for developer efficiency and performance oriented infrastructure products
• Understands how inference frameworks use compiler technology — where they adopt torch.compile, where they go around it, and why
• Understands how new hardware features create new compiler requirements
• Can write clear, defensible strategy documents and knows how to scope an early-access release
• Strong instinct for where to concentrate investment vs. spread it

Ways To Stand Out From The Crowd

• Deep understanding of the PyTorch compiler stack and how to influence strategy in this ecosystem
• Worked on how agents participate in systems-level optimization workflows
• Familiarity with MLIR-based compiler infrastructure and how it maps to NVIDIA hardware primitives
• Reason about inter-kernel optimization tradeoffs to define the right bar for "proven"
• Comfortable reading kernel performance profiles and debugging how torch.compile can help any model

Pay & Benefits

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 - $379,500. You will also be eligible for equity and benefits.