What happens when AI research, GPU infrastructure, and product execution move together? NVIDIA’s AI PMO team helps make that possible. We are looking for a Senior Technical Program Manager to lead strategic AI programs across research, engineering, product, and business teams. We help teams turn sophisticated priorities into clear plans, aligned decisions, and measurable outcomes! This role supports teams building, training, evaluating, optimizing, and deploying sophisticated AI models on NVIDIA’s accelerated computing platform. We’re excited to add a program leader who can make this work clear, coordinated, and durable!
What you'll be doing:
Lead AI initiatives spanning research, software, hardware, infrastructure, product, quality, security, legal, operations, marketing, and developer relations.
Build roadmaps, achievements, ownership models, governance plans, risk tracking, and success metrics.
Partner with technical teams to align model development, training, inference, evaluation, GPU capacity, and production deployment.
Support architecture and integration decisions while resolving cross-team dependencies.
Share clear updates with leaders on progress, tradeoffs, risks, and recommendations.
What we need to see:
10+ years of technical program management, engineering program management, software development, or related experience.
Bachelor’s degree in computer science, engineering, or a related technical field, or equivalent experience.
Experience leading strategic programs across multiple business units, engineering teams, geographies, or corporate functions.
Solid understanding of the AI development lifecycle, including model development, training, evaluation, inference, deployment, and support.
Practical experience with deep learning frameworks, GPU-accelerated computing, distributed systems, modern software development practices, agile development, CI/CD, and tools such as Git, GitHub, GitLab, Jira, Aha!, or Confluence.
Ways to stand out from the crowd:
Experience leading AI platform, infrastructure, developer ecosystem, or product integration initiatives spanning several teams.
Experience working with foundation models, generative AI, multimodal models, agentic systems, or open-source AI communities.
Knowledge of GPU architecture, distributed training, high-performance computing, Kubernetes, workload schedulers, cloud infrastructure, or data-center infrastructure.
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.#deeplearningSkills Required
- 10+ years of technical program management, engineering program management, software development, or related experience.
- Bachelor's degree in computer science, engineering, or a related technical field, or equivalent experience.
- Experience leading strategic programs across multiple business units, engineering teams, geographies, or corporate functions.
- Solid understanding of the AI development lifecycle, including model development, training, evaluation, inference, deployment, and support.
- Practical experience with deep learning frameworks, GPU-accelerated computing, and distributed systems.
- Practical experience with modern software development practices, agile development, and CI/CD.
- Practical experience with tools such as Git, GitHub, GitLab, Jira, Aha!, or Confluence.
- Experience supporting architecture and integration decisions and resolving cross-team dependencies.
- Experience building roadmaps, ownership models, governance plans, risk tracking, and success metrics.
- Experience leading AI platform, infrastructure, developer ecosystem, or product integration initiatives spanning several teams.
- Experience with foundation models, generative AI, multimodal models, or agentic systems.
- Knowledge of GPU architecture, distributed training, high-performance computing, Kubernetes, workload schedulers, cloud infrastructure, or data-center infrastructure.
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.”
