Senior Emulation Power Engineer

Reposted 12 Days Ago
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Santa Clara, CA
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The Senior Emulation Power Engineer will analyze power data, develop methodologies for energy efficiency, and collaborate with various engineering teams to enhance NVIDIA products' power consumption.
Summary Generated by Built In

We are looking for a Senior Emulation Power Engineer! NVIDIA prides in having energy efficient products. We believe that continuing to maintain our products' energy efficiency compared to competition is key to our continued success.

Our team is responsible for analyzing fullchip and unit-level power data and driving ASIC teams to improve their units’ power efficiency; and is responsible for researching, developing, and deploying methodologies to help NVIDIA's products become more energy efficient. Key responsibilities include developing techniques to model, analyze, and reduce power consumption of NVIDIA GPUs. As a member of the Emulation Power Team, you will collaborate with Architects, Performance Engineers, Software Engineers, ASIC Design Engineers, Product teams and Physical Design teams to study and implement Emulation methodologies to capture Benchmark Power, perform power analysis and case studies for NVIDIA's next generation GPUs and Tegra SOCs. Your contributions will help us gain early insight into energy consumption of graphics and artificial intelligence workloads, and will allow us to influence architectural, design, and power management improvements.

What You'll Be Doing:

  • Use Emulation platforms like Zebu and Palladiums to emulate benchmark traces.

  • Develop testbench capabilities to fast track and automate emulation waveform captures.

  • Use internally developed tools and industry standard pre-silicon Gate-level and RTL power analysis tools, to help report power.

  • Perform comparative power analysis, to spot trends and anomalies, that warrant more scrutiny.

  • Interact with Architects and RTL designers to help them interpret their power data and identify power bugs; drive them to implement fixes.

  • Select and run a wide variety of workloads for power analysis.

  • Prototype a new architectural feature in Verilog and analyze power.

What We Need To See:

  • BS or MS (or equivalent experience) with 5+ years of experience or PhD in related fields.

  • Strong analytical skills, attention to detail, systematic approach to debug and curiosity to learn.

  • Strong coding/automation skills, preferably in Python, and/or C++.

  • Background in emulation with intent to perform hand on debug on daily basis.

  • Good understanding of concepts of energy consumption, estimation, data movement and low power design.

  • Familiarity with Verilog and ASIC design principles, including knowledge of Power Artist, PTPX (Prime Power RTL, RTL Architect).

  • Good verbal/written English and interpersonal skills; much collaboration with design teams is expected.

  • Desire to bring data-driven decision-making and analytics to improve our products.

The base salary range is 136,000 USD - 264,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

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.

Top Skills

C++
Palladium
Power Artist
Ptpx
Python
Verilog
Zebu
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The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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