Senior Product Manager - AI Platform Inference
US, CA, Santa ClaraPosted Aug 5, 2026
Overview
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Inference is the fastest growing and most competitive area in Generative AI today. It is where AI models impact our daily life, and where ever bit of accuracy and performance matters for quality, safety, and cost. Inference is also constantly evolving, with new acceleration algorithms, usecases, and deployment techniques. As a Senior Product Manager for AI Platform Inference you will be responsible for building the tools, SDKs, and libraries which enables developers' Inference deployments to thrive on NVIDIA GPUs.
As NVIDIA Product Managers, our goal is to enable developers to be successful on the NVIDIA Platform, and push the boundaries of what is possible with their AI deployments! For Inference, we are the champions inside NVIDIA for AI developers looking to accelerate their deployments on GPUs. We work directly with developers inside and outside of the company to identify key improvements, create roadmaps, and stay alert on the inference landscape. We also work with NVIDIA leaders to define clear product strategy, and marketing team teams to build go-to-market plans. The Product Management organization at NVIDIA is a small, strong, and impactful group. We focus on enabling deep learning across all GPU use cases and providing great solutions for developers. We are seeking a rare blend of product skills, technical depth, and passion to make NVIDIA great for developers. Does that sounds familiar? If so, we would love to hear from you!
What you'll be doing:
• Create products to help developers build better Inference deployments
• Develop product strategy, roadmaps, and go-to-market plans
• Collaborate with internal and external developers to build product-based roadmaps for model optimization software
• Work with leadership to align with and drive company strategy
What we need to see:
• Experience with Inference deployment and optimization software (ex. vLLM, SGLang, FlashInfer, TensorRT-LLM, Triton, Dynamo, TorchAO, etc.)
• Demonstrable knowledge of GenAI or machine learning concepts, particularly around performance optimization, and software development and delivery
• BS or MS degree in Computer Science, Computer Engineering, or similar experience (or equivalent experience)
• 6+ years of technical product management, or similar, experience at a technology company
• Strong communication and interpersonal skills
Ways to stand out from the crowd:
• Experience leading optimization products for Inference
• Working on Open Source & Github-first developer products with deep customer interactions
• Knowledge of GPU architecture, HW/SW co-design, and performance profiling
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.
Applications for this job will be accepted at least until August 9, 2026.
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.
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Original posting: jobs.nvidia.com
RISC-V ecosystem
NVIDIA Corporation in the RISC-V ecosystem
RISC-V International: Premier Board
Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.
- NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
- Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
- Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage
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