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Manager, GPU Accelerated Data Analytics

NVIDIA· Mgmt, Dev Tech SW
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Hybrid (Santa Clara, CA), Remote, New York, NY$224k - $356.5k + equityFull-timePosted 7mo ago

About the role

Lead a distributed team of performance engineers to optimize CPU/GPU workloads, collaborate with developers, and advance NVIDIA’s hardware-software platforms for accelerated data analytics in data centers.

Responsibilities

  • Driving Innovation: researching, analyzing, and developing techniques to optimize performance of complex workloads across cloud and on-premise environments; inventing new algorithms and collaborating with architects to influence hardware.
  • Technical Leadership: leading software design decisions, influencing architecture roadmap, and communicating technical solutions to multi-functional teams; prioritizing and leading key initiatives to advance performance and adoption of NVIDIA’s hardware and software platforms.
  • Growing and Mentoring Your Team: building a distributed world-class team of performance engineers; growing domain, hardware and software expertise; fostering a collaborative and innovative culture.
  • Collaboration and Communication: collaborating with company leadership, research teams, and cross-functional partners; driving strategic decision-making and program management; advocating for next-generation hardware and software products.

Qualifications

  • MS or PhD in Computer Science, Computer Engineering, or related computational science degree (or equivalent experience).
  • 7+ overall years of relevant experience with 4+ years in a technical role and 3+ years in engineering leadership.
  • Outstanding leadership, cross-functional collaboration, and impactful project execution.
  • Hands-on experience in low-level performance optimization, including GPU parallel programming (e.g., CUDA).
  • Programming fluency in C/C++ with deep understanding of algorithms and software development.
  • In-depth expertise with CPU and GPU architecture fundamentals.
  • Strong algorithmic skills and experience implementing low-level optimizations for enterprise applications.
  • Track record of building high-performing teams by hiring top engineering talent.
  • Excellent communication and presentation skills.
  • Demonstrated ability to plan, lead, and execute high-impact initiatives.

Skills

Required:GPU parallel programmingC/C++CPU/GPU architecture

Benefits

  • equity
  • benefits (as described in posting)
Last updated Aug 7, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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