AI and ML Power Methodology Engineer

at Nvidia

USD 136,000-264,500 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 4 Algorithms @ 7 Data Analysis Data Pipelines Data Structures @ 7 Debugging Deep Learning GPU GenAI Generative AI LLM Machine Learning @ 4 Python @ 6 RAG @ 3 Vector Databases @ 3

Details

NVIDIA's Power Team researches and develops methodologies to improve product energy efficiency. This role develops AI-powered methods and tools to enhance power analysis and optimization for future graphics and AI solutions. The position involves close collaboration with hardware, machine learning, and infrastructure teams to understand energy usage in graphics and AI workloads and improve architecture, design, and power management.

Responsibilities

Research, develop, and own advanced AI, machine learning, and deep learning methodologies for estimating pre-silicon power and improving GPU energy efficiency.
Develop tools for gathering, building, and annotating domain-specific datasets used to train large language models for different tasks, tools, and applications.
Leverage generative AI technologies to solve complex problems in chip design and drive innovation 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 sources such as silicon and emulation for advanced data-dependent methodologies.
Design LLM-based tools 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.

Requirements

A master's degree or equivalent experience, with proven relevant experience, or a PhD in a related field.
At least 5 years of experience.
Proficiency in rapid prototyping using languages such as Python and C++.
Strong foundational knowledge of data structures, algorithms, and software engineering principles.
Familiarity with training and fine-tuning large language models, advanced RAG pipelines, vector databases, and agentic frameworks.
Ability to formulate and analyze algorithms and assess their runtime and memory complexities.
Interest in applying quantitative decision-making and analytics to improve product energy efficiency.
Good verbal and written English and interpersonal skills.

Compensation and Benefits

The base salary is determined by location, experience, and the pay of employees in similar positions. The base salary range is USD 136,000–218,500 for Level 3 and USD 168,000–264,500 for Level 4. The role also includes eligibility for equity and benefits. Applications will be accepted at least until August 8, 2026.