Used Tools & Technologies
Not specified
Required Skills & Competences ?
Machine Learning @ 3 Product Management @ 5 System Architecture @ 3 LLM @ 6 GPU @ 3Details
NVIDIA's Accelerated Computing team is focused on Machine Learning, Artificial Intelligence and High-Performance Computing. The team seeks a capable individual with a track record in technology and skills for GPU product definition for Data Center. The role requires understanding how GPU architecture affects datacenter application performance and the economics of data center workloads, and translating analyses into product proposals and clear recommendations for technical and non-technical audiences.
Responsibilities
- 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 discovery of opportunities for innovation in GPU, system, and data-center architecture by analyzing data center workload trends, Deep Learning research, analyst reports, competitive landscape, and token economics.
- Find opportunities where NVIDIA can uniquely address customer needs and translate these into compelling GPU value propositions and product proposals.
- Distill sophisticated analyses into clear recommendations for both technical and non-technical audiences.
Requirements
- 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 is 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 the 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
- 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 performance engineers, hardware architects, and product managers.
Compensation & Benefits
- Base salary ranges provided by location and level: 144,000 USD - 218,500 USD (Level 3); 168,000 USD - 258,750 USD (Level 4).
- You will also be eligible for equity and benefits (see https://www.nvidia.com/en-us/benefits/).
Location & Time Type
- Location: Santa Clara, California, United States.
- Time type: Full time.
Other
- Applications accepted at least until September 20, 2025.
- NVIDIA is an equal opportunity employer and committed to fostering a diverse work environment.