Data Analytics CPU Workload Performance Product Manager
NVIDIA
Data Analytics CPU Workload Performance Product Manager
NVIDIA
Designs the chips and software that power AI
We're building a new generation of data center CPUs at NVIDIA — Vera, Grace, and future designs purpose-built for accelerated computing and the workloads defining infrastructure. Data analytics is one of the highest-value arenas for CPU performance, and we need someone to own NVIDIA's strategy and value proposition there! This role sits at the nexus of go-to-market, software architecture, platform architecture, performance measurement, and competitive positioning — making it a true workload strategy role, not a benchmark-running one. From TPC-H and TPC-DS methodologies to collaborative solutions with the world's leading database and analytics vendors, the scope is broad and the impact is real. We're looking for a product manager who deeply understands how CPUs win in practice and can turn that insight into roadmap decisions, customer proof points, and field-ready positioning.
What you'll be doing:
What we need to see:
Ways to stand out from the crowd:
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.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.
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