Senior Technical Program Manager, Deep Learning Initiatives

NVIDIA's AI PMO team is seeking a Senior Technical Program Manager to lead strategic AI programs across research, engineering, product, and business teams. The successful candidate will help teams turn sophisticated priorities into clear plans, aligned decisions, and measurable outcomes.

Responsibilities

• 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.

Requirements

• 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.

Nice to Have

• 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.