Senior Technical Product Manager - AI Infrastructure

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Senior Technical Product Manager at NVIDIA focused on AI Infrastructure, driving the roadmap for Enterprise Infrastructure products like NVIDIA DGX and Networking. The role involves defining product strategy, creating go-to-market collateral, and engaging with customers and internal teams to improve AI developer efficiency and data center solutions. Requires deep understanding of AI/ML infrastructure, HPC, cloud technologies, and AI/ML concepts like LLMs and Gen AI.

What you'd actually do

  1. Define product strategy and solutions for NVIDIA's Enterprise Infrastructure products using NVIDIA DGX and NVIDIA Networking.
  2. Create GTM Collaterals and evangelize to the customers.
  3. Distill insights from strategic customers and partners to define, prioritize and complete product roadmaps.
  4. Engage with internal collaborators and ecosystem partners to define solutions that improve customer experience and efficiency at the data center solution level
  5. Create GTM Collaterals and act as the evangelist with sales and marketing teams for new DGX solutions

Skills

Required

  • Product Management Experience
  • Technical Expertise
  • AI/ML Knowledge
  • Leadership and Collaboration
  • Strategic and Analytical Thinking
  • Understanding of the Product Lifecycle

Nice to have

  • Familiarity with the MLOps and LLMOps ecosystem and experience building integrations with popular enterprise platforms
  • Experience deploying systems at scale in modern data center environments
  • Used or built Gen AI services to automate a business need or information retrieval
  • Deep experience in Linux and OSS automation tools

What the JD emphasized

  • BS or MS degree in Computer Science, Computer Engineering, or similar field (or equivalent experience) and 12+ years of product management, or similar, experience at a technology company serving enterprises
  • Proven track record in product management, particularly within the technology sector, with experience serving enterprise customers.
  • Deep understanding of AI/ML infrastructure, high-performance computing (HPC) and networking ; cloud technologies (IaaS, PaaS) such as containerization, Kubernetes and automation tools
  • Familiarity with the MLOps and LLMOps ecosystem and experience building integrations with popular enterprise platforms
  • Used or built Gen AI services to automate a business need or information retrieval

Other signals

  • drive the roadmap and deliver features
  • AI training software
  • AI developer efficiency
  • AI/ML infrastructure
  • AI/ML training and inference
  • Large Language Models (LLMs)
  • Generative AI (Gen AI)