Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world.
Our team is privileged to work on Power Optimization of Data center, gaming and automotive GPU chips. We also work on power optimization of Networking chips. The gamut of GPUs and networking chips requires the team to provide architecture, micro-architecture, RTL Design, methodology and AI based power optimization solutions. 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 GPUs and Networking products. 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.
Use artificial intelligence to devliver RTL and/or Architecture Power optimization solutions.
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 a new architectural feature in Verilog and analyze power.
What We Need To See:
Pursuing or recently completed a MS or PhD in Electrical Engineering, Computer Engineering, or related fields with coursework or experience in AI, Digital Design and VLSI concepts (or equivalent experience).
Understanding of RTL power optimization fundamentals, including switching activity, clock/enable efficiency, and common low‑power design patterns at the RTL level.
Knowledge of backend flows such as logic synthesis and place‑and‑route, and how RTL decisions impact post‑layout power and timing.
Familiarity with RTL implementation of low‑power techniques (e.g., clock gating, operand isolation, power gating strategies, multi‑VT usage) and their trade‑offs.
Exposure to industry power analysis tools such as PowerArtist, PrimeTime PX, or equivalent, including running power analysis and interpreting reports to guide design changes.
Strong Python programming skills for building automation scripts, data pipelines, and AI/ML‑driven analysis flows for RTL power optimization.
Coursework and/or hands‑on experience in Machine Learning and Artificial Intelligence, with ability to apply ML techniques to EDA and silicon power problems.
Previous experience debugging RTL or gate‑level power anomalies by tracing logic cones, examining activity/toggle data, and identifying root‑cause structures or scenarios.
Strong written and verbal communication skills to document methodologies, present power findings, and explain AI/ML‑based insights to both design and tools teams.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 116,000 USD - 189,750 USD for Level 2, and 136,000 USD - 218,500 USD for Level 3.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
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
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.”
