Senior Applied Power Architect - GPU
NVIDIAJob Title
Senior Applied Power Architect - GPU
Role Summary
The Senior Applied Power Architect will define methodologies and implement solutions to optimize power, performance, and electrical integrity for next-generation GPU architectures. The role collaborates with ASIC designers, power-integrity, packaging, and product engineers to resolve electrical, thermal, and packaging constraints across chip and board levels.
Experience Level
Senior - posting requests 6+ years of relevant industry experience.
Responsibilities
Primary responsibilities include architecture, analysis, and cross-discipline coordination to meet power and electrical targets for GPU products.
- Invent methodologies, features, and techniques to address electrical, speed, and power challenges for next-generation AI GPU architectures.
- Drive power-management initiatives to optimize perf/watt while meeting electrical and thermal constraints.
- Analyze process characteristics and V–F tradeoffs, including the impact of Vt choices on power and performance.
- Investigate multi-die technologies and propose solutions for packaging, interconnect, physical design, electrical, and thermal challenges.
- Analyze peak current, Di/Dt, IR drop, and EM requirements; specify mitigations and collaborate with ASIC, power-integrity, packaging, and product teams.
Requirements
Key skills and experience required or strongly preferred. Degrees and equivalent-experience details are listed under Education Requirements below and have been omitted from this section.
- Must-have: 6+ years of relevant industry experience in energy-efficient system or processor design; strong knowledge of performance/power modeling and tradeoffs.
- Must-have: Practical understanding of PDN design and electrical issues such as Di/Dt, undershoot/overshoot, IR, EM, and peak-current analysis/mitigation techniques.
- Must-have: Experience analyzing board-level power issues and interpreting measurements from lab instrumentation (oscilloscopes, DAQ).
- Must-have: Strong collaboration and communication skills; ability to work across engineering disciplines.
- Nice-to-have: Experience with Python and data-analysis libraries (Pandas, NumPy, PyTorch) for modeling or analysis.
- Nice-to-have: Prior exposure to multi-die packaging, interconnect, and related physical-design challenges.
Education Requirements
MSEE / MSCE preferred; PhD preferred when available, or equivalent practical experience. Specialization or substantial experience in low-power processor architectures, power-delivery networks, or related electrical/processor architecture fields is expected.
About the Company
Company: NVIDIA
Headquarters: Santa Clara, California, USA
NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.
