We are looking for a technical and hands-on Product Manager to lead our product efforts for local AI on Linux and developers. Client AI is the technology platform on top of NVIDIA's client hardware — GeForce RTX, RTX PRO, DGX Spark, DGX Station, and N1X — that enables AI and agents, content creation, and developer workflows. This Product Manager will define how developers, researchers, and enterprise teams build, run, and deploy AI on NVIDIA client platforms running Linux, with a strong focus on enterprise.
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. Inference stacks like vLLM, SGLang, TensorRT-LLM, and PyTorch are becoming the default runtime for these workflows. This Product Manager will help NVIDIA win the Linux side of this shift — making our client platforms the best place to build and run modern AI.
What you'll be doing:
Define and lead the enterprise agent use case — understand how enterprises deploy agents on-prem, what they need from the platform, and where NVIDIA should invest.
Collaborate with Product Managers that are working on cloud inference backends (vLLM, SGLang, TensorRT-LLM, and PyTorch) to drive and prioritize requirement for local AI.
Own the product strategy and roadmap for the Linux developer experience on NVIDIA client platforms (DGX Spark, DGX Station, RTX PRO workstations, RTX Spark).
Research the developer and enterprise AI ecosystem: interview customers, build personas and user journeys, and map workflows across training, fine-tuning, inference, and agent deployment.
Work hands-on with the latest models, frameworks, and agent tooling so you can represent the developer's point of view in every decision.
Lead cross-functional teams — engineering, DevRel, marketing, partnerships — to ship features and grow adoption.
Influence NVIDIA's GPU, system, and software roadmaps based on what Linux developers and enterprise AI teams actually need.
Build product positioning, technical demos, and sales and partner enablement material for a developer audience.
What we need to see:
8+ years of product management experience, with meaningful time on AI/ML, developer tools, or infrastructure products.
First-hand experience as a developer or engineer — you have shipped code in production and can debug a CUDA, PyTorch, or Docker issue alongside an engineer, not just manage around it.
Deep familiarity with modern AI workflows: training and fine-tuning, inference serving, agent frameworks, RAG pipelines, and evaluation.
Working knowledge of at least one major inference backend (vLLM, SGLang, TensorRT-LLM, or PyTorch-based serving).
Fluency in Linux as a development and deployment environment.
Strong written communication and the ability to translate technical depth for both engineers and executives.
Bachelor's degree in Computer Science, Electrical Engineering, or equivalent experience.
Ways to stand out from the crowd:
Prior role as an AI/ML engineer, inference systems engineer, or application developer building with LLM APIs and agent frameworks (LangChain, LlamaIndex, MCP).
Experience with model optimization — quantization, distillation, speculative decoding, KV-cache strategies.
Hands-on with CUDA, Triton, or low-level GPU programming.
Background in enterprise software, on-prem deployments, or private AI.
Open-source contributions to AI/ML, inference, or agent projects.
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 258,750 USD for Level 4, and 208,000 USD - 327,750 USD for Level 5.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
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.Skills Required
- 8+ years of product management experience
- Experience in AI/ML, developer tools, or infrastructure products
- Bachelor's degree in Computer Science, Electrical Engineering, or equivalent experience
- First-hand experience as a developer or engineer
- Deep familiarity with modern AI workflows
- Working knowledge of at least one major inference backend
- Fluency in Linux as a development and deployment environment
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
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.”
