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 develop and implement methodologies that leverage innovative AI advancements to enhance Nvidia's power team capabilities.

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As an essential part of our Power Team, you'll closely collaborate with HW/ML experts and infrastructure teams. You'll work together to create new and improved ways to fix and improve power for NVIDIA's future AI solutions. Your contributions will help us understand energy usage in graphics and AI workloads and make improvements in architecture, design, and power management.

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What you'll be doing:

• Research, develop and own advanced AI/ML/DL methodologies to estimate pre-silicon power and improve GPU energy efficiency.
• Develop tools that will help in the gathering, building, and annotation of domain specific datasets to train LLMs for different tasks, tools, and applications.
• Make a difference by leveraging Gen AI technologies to solve complex problems in chip design, driving innovation and meaningful impact across the Power team.
• Develop tools for training and fine-tuning large language models, advanced Retrieval-Augmented Generation (RAG) pipelines, vector databases and agentic frameworks.
• Build efficient data pipelines to gather power data from different sources, such as silicon, emulation, for developing advanced data-dependent methodologies.
• Design tools using LLMs to analyze power patterns, generate optimized code, and provide actionable insights for power debugging and optimization.
• Enable efficient storage and retrieval of data from databases.
• Develop user-friendly data visualizations to simplify data analysis and insight generation.

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What we need to see:

• MS (or equivalent experience) with proven experience or PhD in related fields.
• 2+ years of experience.
• Proficiency in rapid prototyping using languages like Python and C++, with strong foundational knowledge of data structures, algorithms, and software engineering principles.
• Familiarity with training and fine-tuning large language models, advanced Retrieval-Augmented Generation (RAG) pipelines, vector databases and agentic frameworks.
• Ability to formulate and analyze algorithms, and comment on their runtime and memory complexities.
• Desire to bring quantitative decision-making and analytics to improve the energy efficiency of our products.
• Good verbal/written English and interpersonal skills.