At NVIDIA, we are building the foundation & blueprints for how AI workloads are served at scale for NVIDIA employees and DSX Partners. As a Product Manager for Inference Platform, you will help define and drive the products and platform capabilities that enable large-scale models serving across a broad portfolio of models, both open source and proprietary. You will work at the intersection of AI research, infrastructure engineering, and real user needs, shaping how inference is delivered reliably, efficiently, and at scale.
This is high-impact role. You will be expected to bring structure to undefined problem spaces, make progress without complete information, and build conviction through deep engagement with users, engineers, and the broader ecosystem of AI Cloud partners. The right candidate is equally comfortable discussing model serving architecture, token economics and writing a clear product brief.
What you will be doing:
- Define product vision and strategy for inference platform capabilities — including APIs, capacity management, cost management, performance and optimization, and model serving infrastructure.
- Translate user needs and infrastructure constraints into clear requirements and prioritized roadmaps.
- Partner closely with engineering, research, and user groups teams to drive execution from concept through launch.
- Be responsible for end-to-end product lifecycle for inference-related products and platform investments.
- Develop deep understanding of the inference ecosystem — model formats, serving frameworks, API formats, and the tradeoffs that matter at scale.
- Drive clarity in ambiguous situations by framing the problem, identifying what is known and unknown, and proposing a path forward.
- Represent the voice of the user and ensure product decisions are grounded in real needs, not assumptions.
- Track and synthesize developments across the inference landscape: open source model releases, serving frameworks, competitive dynamics, and emerging use cases.
What we need to see:
- 12+ years of experience with a track record of delivering complex technical products.
- Bachelors degree or higher, or equivalent experience
- Strong written and verbal communication, you are able to write clear, concise product documents, specs, and strategies.
- Ability to operate in ambiguous, fast paced environments and make progress without a full playbook.
- Analytical professional who can break down complex problems, identify the right questions, and drive toward decisions.
- Strong user empathy — able to synthesize qualitative and quantitative signals into a coherent picture of what users need and why.
- Deep familiarity with AI/ML systems and inference serving frameworks (such as TensorRT-LLM, vLLM, or Triton Inference Server), tradeoffs involved, and what matters to model publishers, application developers and cloud operators.
- Experience with inference APIs- design, versioning, performance, hardware efficiency, and developer experience.
- Familiarity with open source as well as commercial model ecosystems and the different considerations each brings to a serving platform.
Ways to stand out from the crowd:
- Experience with sophisticated inference techniques: disaggregated prefill/decode, KV cache management, speculative decoding, or continuous batching.
- Background in large scale systems and developer platforms, cloud infrastructure, or MLOps tooling.
- Exposure to capacity planning, quota management, or resource scheduling in large-scale compute environments.
You thrive in the early stages of building — where the problem is not fully defined, the team is still forming, and the decisions you make will shape direction for years. You don't wait for perfect information. You ask good questions, build conviction incrementally, and create momentum. You can balance user's reality and engineering constraints simultaneously. You bring clarity and cut through noise. You have a genuine curiosity about how inference works. You care about users’ needs beyond trivia, as it improves your product.
#LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 208,000 USD - 327,750 USD for Level 5, and 240,000 USD - 379,500 USD for Level 6.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 an inclusive 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
- 12+ years of experience delivering complex technical products
- Bachelor’s degree or higher, or equivalent experience
- Strong written and verbal communication skills, including clear product documents, specifications, and strategies
- Ability to operate in ambiguous, fast-paced environments and make progress without a complete playbook
- Strong analytical skills and ability to break down complex problems and drive decisions
- Strong user empathy and ability to synthesize qualitative and quantitative signals
- Deep familiarity with AI/ML systems and inference serving frameworks such as TensorRT-LLM, vLLM, or Triton Inference Server
- Experience designing and managing inference APIs, including versioning, performance, hardware efficiency, and developer experience
- Familiarity with open-source and commercial model ecosystems
- Experience with disaggregated prefill/decode, KV cache management, speculative decoding, or continuous batching
- Background in large-scale systems, developer platforms, cloud infrastructure, or MLOps tooling
- Exposure to capacity planning, quota management, or resource scheduling in large-scale compute environments
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.
-
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.
-
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.
-
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.”
