AI and ML Power Methodology Engineer

Nvidia Corporation in; Santa Clara (CA); On-site; USD 136,000 - 265,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking an AI/ML Power Methodology Engineer (Finance) to research, develop, and own advanced AI/ML methods that estimate pre-silicon power and improve GPU energy efficiency. You will build tools to gather and annotate domain datasets to train LLMs for various tasks, and apply Gen AI to chip design challenges within the Power team.

You will train and fine-tune large language models, implement RAG pipelines, work with vector databases, and design data pipelines for power data across

Qualifications

• MS (or equivalent) with proven experience or PhD in related fields.
• 5+ 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.

Responsibilities

• 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.

Skills

Python

C++

Data structures & algorithms

English communication

Rapid prototyping

Education

MS or PhD in related fields

Tools

RAG pipelines

Vector databases

Agentic frameworks

LLMs

Job description

AI and ML Power Methodology Engineer (Finance)

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.

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.

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.

What we need to see:

• MS (or equivalent experience) with proven experience or PhD in related fields.
• 5+ 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.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4.

You will also be eligible for equity and benefits .

Applications for this job will be accepted at least until August 8, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.