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Job description
NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people! Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world!
What You’ll Be Doing
Guide the architecture of the next-generation of GPUs through an intuitive and comprehensive grasp of how GPU architecture affects performance for datacenter applications, especially Large Language Models (LLMs)
Drive the discovery of opportunities for innovation in GPU, system, and data‑center architecture by analyzing the latest data center workload trends, Deep Learning research, analyst reports, competitive landscape, and token economics
Find opportunities where we uniquely can address customer needs, and translate these into compelling GPU value proposition and product proposals
Distill sophisticated analyses into clear recommendations for both technical and non‑technical audiences
What We Need To See
5+ years of total experience in technology with previous product management, AI related engineering, design or development experience highly valued
BS or MS or equivalent experience in engineering, computer science, or another technical field. MBA a plus.
Deep understanding of fundamentals of GPU architecture, Machine Learning, Deep Learning, and LLM architecture with ability to articulate relationship between application performance and GPU and data center architecture
Ability to develop intuitive models on the economics of data center workloads including data center total cost of operation and token revenues
Demonstrated ability to fully contribute to above areas within 3 months
Strong desire to learn, motivated to tackle complex problems and the ability to make sophisticated trade‑offs
Ways To Stand Out From The Crowd
2+ years direct experience in developing or deploying large scale GPU based AI applications, like LLMs, for training and inference
Ability to quickly develop intuitive, first‑principles based models of Generative AI workload performance using GPU and system architecture (FLOPS, bandwidths, etc.)
Comfort and drive to constantly stay updated with the latest in deep learning research (academic papers) and industry news
Track record of managing multiple parallel efforts, collaborating with diverse teams, including performance engineers, hardware architects, and product managers
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 148,000 USD - 224,250 USD for Level 3, and 168,000 USD - 258,750 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until January 16, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.
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Worksite address
santa clara, CA, 95053, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.