NVIDIA
Manager, GPU Accelerated Data Analytics
$224K–$431K
US, CA, Santa Clara +2 · Manager · Full-time · Posted Aug 5, 2026
- Location
- US, CA, Santa Clara
US, CA, Remote
US, NY, New York - Experience
- 7+ overall years of relevant experience, including 4+ years in a technical role and 3+ years in an engineering leadership role.
- Education
- MS or PhD in Computer Science, Computer Engineering, or a related computationally focused science degree (or equivalent experience).
About the job
Leads performance engineers developing and optimizing GPU- and CPU-accelerated data analytics and other enterprise workloads, while advancing NVIDIA platform adoption and team capabilities.
What you'll do
- Research and develop performance optimizations for complex workloads across cloud and on-premise environments, including algorithms and hardware collaboration.
- Lead software design, technical initiatives, architecture influence, and cross-functional execution.
- Build, mentor, and grow a distributed team of performance engineers.
What they ask for
- Hands-on low-level performance optimization, including GPU parallel programming such as CUDA.
- Programming fluency in C/C++ and deep understanding of algorithms and software development.
- In-depth knowledge of CPU and GPU architecture fundamentals and experience implementing low-level optimizations for enterprise applications.
- Demonstrated engineering leadership, team building, collaboration, communication, and execution of high-impact initiatives.
Nice to have
- Experience leading engineering teams to design performance-first prototypes.
- Background in distributed high-performance data analytics, SQL or vector databases, or modern data center network and storage technologies.
Pay
224,000 USD - 356,500 USD (base salary, Level 3); 272,000 USD - 431,250 USD (base salary, Level 4)
Tools
CUDA, C/C++, SQL
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