Senior Product Manager – Local AI GPUs

NVIDIA•Us, CA

About The Position

NVIDIA is the engine behind modern agentic AI - from frontier model training and inference to accelerated data analytics, simulation, both in the cloud as well as locally at the edge. We are looking for a technical and hands-on Senior Product Manager who can turn the needs of developers, researchers, and enterprises into product requirements for personal AI systems and help define, build, and launch the next generation of GPU products for Local AI. Generative AI is moving from the cloud to the workstation and the edge. Developers want to prototype, fine-tune, and run frontier models locally. Enterprises want to deploy agents against their private data on-prem. This Product Manager will make our Local AI platforms the best place to build and run modern AI. You will build GPU architectures, platform integration, and go-to-market strategy for some of the most fast-paced compute environments in the world.

Requirements

8+ years in product management, with meaningful time on compute products, AI/ML, developer tools, or infrastructure products.
Strong understanding of AI accelerator architectures and the factors that affect AI inference performance.
Proven ability to take products from concept → launch → customer adoption at scale.
Strong product judgement with capacity to make clear tradeoffs among performance, memory capacity, power, cost, and user experience
A strong mix of technical depth and strategic/business insight.
Highly analytical.
Able to balance multiple projects at the same time.
Excellent communication skills and the ability to work cross-functionally across engineering, operations, and customer teams.
Bachelor's Degree or equivalent experience

Nice To Haves

Hands-on experience with local AI workloads and agents.
Familiarity with enterprise AI deployment challenges and needs.
Demonstrated success defining & positioning hardware/software compute platforms.
MBA preferred

Responsibilities

Own the full product lifecycle related to Local AI offerings —architecture definition, feature prioritization, roadmap, launch, and scale-out adoption.
Define hardware, system, and software requirements across compute, networking, storage, and security to support agentic AI & simulation workloads.
Translate real workloads into targets for model capacity, latency, efficiency, memory, bandwidth, power, and cost.
Study developer workflows on Windows and Linux, including how popular models and inference frameworks run on NVIDIA platforms.
Partner with OEMs & customers to capture requirements, validate builds, and ensure platform success in diverse deployment environments.
Conduct market and competitive analysis to drive next-generation GPU, interconnect, and system strategy.
Drive alignment with engineering, architecture, operations, and supply chain teams to deliver products on time and at scale.
Build technical collateral (white papers, briefs, specifications, solution guides) and support customer-facing engagements.
Position NVIDIA’s accelerated compute solutions to technical and executive audiences, articulating performance, TCO, and AI workload benefits.