Nvidia Power Methodology Modeling Engineer - New College Grad 

United States, Texas 

996000816

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 PhD in related fields or equivalent experience.

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

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

• 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.