At NVIDIA, we pride ourselves in having energy-efficient products. We believe that continuing to maintain our products' energy efficiency compared to the competition is key to our continued success. Our team researches and develops methods to make NVIDIA's products more energy efficient. We deliver power and energy models that work with performance simulators, RTL simulation, emulation, and silicon platforms.

As a member of the Architecture Energy Modeling Team, you will collaborate with Architects, ASIC Design Engineers, Low Power Engineers, Performance Engineers, Software Engineers, and Physical Design teams to study and implement energy modeling techniques for NVIDIA's next generation GPUs, CPUs and Tegra SOCs. Your contributions will help us understand energy usage in graphics and AI workloads and make improvements in architecture, design, and power management.

What you'll be doing:

• Define and implement tools and methodologies for efficient data generation from post layout netlists to feed into data movement power analytical model.

• Develop tools and infrastructure to sanitize each metric in the model to achieve high correlation accuracy.

• Define and implement tools and methodologies for efficient integration of power models with performance tools.

• Identify runtime and memory limitation of existing flows and tools to speedup model delivery process.

• Mine data from pre- and post-silicon performance runs to find important data paths and bottlenecks. Give feedback to design teams and improve power efficiency.

• Work with floorplan, performance, verification and emulation methodology and infrastructure development teams to integrate data movement power models.

• Experiment with various ML techniques to answer what-if design questions and set proper power/energy targets for next generation chips.

• Enable efficient storage and retrieval of data from database.

• Enable easy visualization of data using platforms such as PowerBI, OpenSearch.

What we need to see:

• MS (or equivalent experience) with 3 years of experience or PhD in related fields.

• Strong coding skills, preferably in Python, C++.

• Ability to formulate and analyze algorithms, and comment on their runtime and memory complexities.

• Strong understanding of VLSI, digital design, and computer architecture concepts.

• Basic understanding of fundamental concepts of power and energy consumption, estimation, and low power design.

• Basic understanding of chip design process from RTL design to tape-out.

• Background in machine learning, AI, and/or statistical modeling is a plus.

• Desire to bring quantitative decision-making and analytics to improve the energy efficiency of our products.

• Good verbal/written English and interpersonal skills.

The base salary range is 128,000 USD - 258,750 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.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.