Senior Applied Power Architect - GPU

$168k - $311k • Remote • US, CA, Santa Clara

Posted 14d ago

Job Location

US, CA, Santa Clara

Tech Stack

Remote Work Policy

Fully remote

Categories

Machine Learning Engineer

About the job

NVIDIA is seeking a Senior Applied Power Architect to join our Applied Power Architecture team. You will be instrumental in developing state-of-the-art GPUs for AI, Automotive, GeForce, and Mobile products. This role involves inventing methodologies, features, and techniques to tackle electrical, speed, and power challenges for next-generation AI architectures. You will drive power management initiatives to optimize efficiency and performance while adhering to electrical, thermal, and power constraints. The position requires a deep understanding of process characteristics and their impact on voltage-frequency (V-F) tradeoffs, as well as investigating multi-die technologies and proposing innovative solutions for packaging, interconnect, physical design, electrical, and thermal challenges. Collaboration with cross-functional teams, including ASIC designers and packaging experts, is essential for formulating effective solutions.

Responsibilities

  • Invent methodologies, features, and techniques to address electrical, speed, and power challenges for next-generation AI architectures.
  • Drive power management initiatives to optimize power efficiency and performance while addressing electrical, thermal, and power constraints.
  • Analyze voltage-frequency (V-F) tradeoffs considering process characteristics and Vt choices.
  • Investigate multi-die technologies and propose solutions for packaging, interconnect, physical design, electrical, and thermal challenges.
  • Analyze peak current, Di/Dt, IR, and EM requirements.
  • Collaborate with ASIC designers, Power Integrity, Packaging experts, and Product engineers to understand challenges and formulate solutions.

Requirements

  • MSEE/MSCE, preferably PhD, or equivalent experience with a specialization in low-power-processor architectures.
  • Solid understanding of energy-efficient system design fundamentals, performance/power modeling, and related tradeoffs.
  • 6+ years of relevant industry experience.
  • Background in PDN design and understanding of electrical issues such as Di/Dt, undershoot/overshoot, IR, EM, and peak current analysis/mitigation techniques.
  • Exposure and working knowledge of Python and data analysis packages like Pandas, NumPy, PyTorch.
  • Exposure to lab setup including power measurement equipment and ability to analyze board-level power issues.
  • Strong interpersonal and organizational skills and ability to work as a teammate.

Benefits

  • Equity
  • Benefits

About nvidia

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