We are now looking for a Power Optimization and Analysis Engineer! NVIDIA prides ourselves on having energy-efficient products. We believe that continuing to maintain our products' energy-efficiency compared to competition is key to our continued success. As part of the u/arch team in the Switch group, you will be responsible for analyzing full chip and unit-level power data and driving the FE/BE ASIC teams to improve their units’ power efficiency; you will be 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 Switches product line.
As a member of Switch u/arch Team, you will collaborate with Architects, Performance Engineers, Software Engineers, ASIC Design Engineers, and Physical Design teams to study and implement power analysis and reduction techniques for NVIDIA's next generation switches. 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 internally developed tools and industry standard pre-silicon gate-level and RTL power analysis tools, to help improve product power efficiency.
Develop and share best practices for performing pre-silicon power analysis.
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 new architectural features in Verilog and power analysis.
What We Need To See:
BSC or MS in Computer Engineering or Electrical Engineering
5+ years of experience in chip design
Good and interpersonal skills; much collaboration with design teams is expected.
Familiarity with Verilog and ASIC design or verification.
Desire to bring data-driven decision-making and analytics to improve our products.
Strong coding/automation skills, preferably in Python, Perl, and C++.
Ways to Stand Out From the Crowd:
Experience with Power Artist, PTPX (Prime Power RTL, RTL Architect).
Strong understanding of concepts of energy consumption, estimation, data movement and low power design.
Skills Required
- BSC or MS in Computer Engineering or Electrical Engineering
- 5+ years of experience in chip design
- Familiarity with Verilog and ASIC design or verification
- Strong coding/automation skills, preferably in Python, Perl, and C++
- Good interpersonal and collaboration skills
- Desire to bring data-driven decision-making and analytics
- Experience with Power Artist, PTPX (Prime Power RTL), or RTL Architect
- Strong understanding of energy consumption, estimation, data movement, and low power design
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
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.”
