Senior Technical Product Manager - GPU Direct Storage

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Technical Product Manager for NVIDIA's GPUDirect Storage and cuFile products, focusing on product strategy, customer engagement, and go-to-market for GPU-accelerated storage solutions used in AI and HPC.

What you'd actually do

  1. Collaborate closely with architects, engineers, and researchers to define and evolve the roadmap for GPUDirect Storage and cuFile.
  2. Work directly with customers and developers to understand use cases, pain points, and requirements, ensuring our solutions meet and exceed their expectations.
  3. Lead efforts in launching and positioning products, including collaboration with Marketing, PR, and Sales teams to develop impactful content, technical collateral, and communication strategies.
  4. Create compelling technical content, including blogs, white papers, webinars, and tutorials, highlighting the value and innovation behind our GPUDirect Storage and cuFile offerings.

Skills

Required

  • BS/MS/PhD in Computer Science, Electrical Engineering, Applied Mathematics, or a related technical discipline (or equivalent experience).
  • 12+ yrs of relevant experience
  • Strong technical expertise in accelerated computing and storage, especially GPUDirect Storage, cuFile, or closely related technologies.
  • Demonstrated experience and deep understanding of scientific computing, AI workloads, and high-performance computing (HPC) environments.
  • Exceptional interpersonal skills, capable of articulating complex technical concepts clearly to both technical and non-technical audiences.

Nice to have

  • Proven track record in software development, architecture, or product management for distributed computing or storage solutions.
  • Direct experience working with CUDA, GPU programming, and large-scale data management.
  • Previous roles defining product strategies or requirements in cloud-based or HPC environments.

What the JD emphasized

  • Strong technical expertise in accelerated computing and storage, especially GPUDirect Storage, cuFile, or closely related technologies.
  • Demonstrated experience and deep understanding of scientific computing, AI workloads, and high-performance computing (HPC) environments.