Principal Product Manager, AI Frameworks

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 ecosystem of other OSS frameworks.

As a Principal Product Manager, AI Frameworks, you will build and direct product strategy across the full arc of NVIDIA's PyTorch Compilers team. This involves shipping the latest hardware features in torch.compile today, developing the canonical shared representation across NVIDIA's compiler and runtime ecosystem, and crafting how agents will engage in deep learning performance work in the future.

Key Responsibilities:

• Own the strategy for NVIDIA's PyTorch compiler portfolio, including torch.compile, defining the roadmap and go-to-market for NVIDIA's shared representation layer, and shaping the product vision for agent-native compiler workflows.
• Lead product strategy across the roadmap, defining priorities in close partnership with engineering leads, and translating ecosystem signals into prioritized product decisions.
• Engage directly with customers and partners, representing NVIDIA at PyTorch contributor and ecosystem forums.
• Define success metrics and release criteria, establishing performance gates and adoption milestones.

Requirements:

• 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 and how new hardware features create new compiler requirements.

Nice to Have:

• Deep understanding of the PyTorch compiler stack and how to influence strategy in this ecosystem.
• Experience with how agents participate in systems-level optimization workflows.
• Familiarity with MLIR-based compiler infrastructure and how it maps to NVIDIA hardware primitives.
• Ability to reason about inter-kernel optimization tradeoffs and define the right bar for "proven".

You will also be eligible for equity and benefits.