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NVIDIA

Designs the chips and software that power AI

Data Analytics CPU Workload Performance Product Manager

Technical Product ManagementConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • 12+ years of experience in technical product management, performance engineering, or a closely related area.
  • A BS or MS in Computer Science, Electrical Engineering, or Computer Engineering, or equivalent experience.
  • Comprehensive, practical knowledge of CPU and database performance.
  • Understanding of system hardware characteristics that influence analytics performance, including caching and clustering methods, high availability, memory and I/O sensitivity, and architectural trade-offs.
  • Ability to influence platform and architecture teams by translating workload performance into product, platform, and feature requirements.
  • Experience collaborating with external ISVs, silicon vendors, or the broader analytics ecosystem.

Responsibilities

  • Take responsibility for the workload and market approach for data analytics and data processing on NVIDIA data center CPUs by identifying priority workloads, customer scenarios, and the benchmarks and proof points that should guide the roadmap.
  • Lead the complete lifecycle of benchmarks such as TPC-H and TPC-DS, including methodology, cluster and benchmarking architecture, competitive analysis, and market positioning.
  • Translate disk, cache, memory, I/O, clustering, availability, and software behavior into concrete CPU, platform, and system requirements, then advise architecture and platform teams on what to build and why.
  • Build the quantitative value proposition across performance, infrastructure, software licensing, power, and total cost of ownership to position NVIDIA CPUs against challenging architectures.
  • Work with external ISVs, database and analytics vendors, cloud providers, and strategic customers to verify requirements and build joint solutions and go-to-market approaches.
  • Turn benchmark results and customer evidence into product decisions, competitive reactions, customer proof points, and field enablement materials.

Desired Qualifications

  • Hands-on experience with TPC-H, TPC-DS, or comparable data analytics benchmarks, including methodology development and measurement.
  • Understanding of the disk, cache, and memory sensitivities of database and analytics workloads at scale.
  • Experience with market entry strategies, solution presentation, or the wider data analytics provider and cloud environment.
  • Background in accelerated computing platforms or data center CPU product launches.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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