Senior Power Analysis and Optimization Engineer
$136k - $265k • Remote • US, CA, Santa Clara
Posted 3d ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Categories
LLM Engineer
About the job
We are seeking a Senior Power Architecture & Optimization Engineer to advance energy efficiency through sophisticated analytics and AI, including specialized LLMs for power analysis. This role is central to NVIDIA's mission of creating the most energy-efficient GPUs and SoCs, leveraging AI and LLMs as a key differentiator for future products. You will combine expertise in power architecture with machine learning, reinforcement learning, data analytics, and large language models to innovate in modeling, analyzing, and optimizing energy consumption across various design levels.
Responsibilities
- Analyze full-chip and unit-level power using industry-standard tools and translate data into design improvements.
- Develop and productionize power-aware models and flows using ML/RL for anomaly detection, power management, and design-space exploration.
- Design and train LLMs to interpret power data, identify root causes, propose fixes, and recommend optimizations.
- Perform comparative power analysis across workloads and products to uncover trends and optimization opportunities.
- Collaborate with cross-functional teams to interpret power data, debug power issues, and drive design changes.
- Prototype and evaluate new architectural features for their power and energy implications.
- Automate and scale flows, and define new pipelines for faster power anomaly detection and integration of AI models with design decisions.
- Apply AI to power optimization by building and deploying models to recommend or tune power-efficient configurations.
Requirements
- MS (or equivalent experience) and 5 years of experience, OR PhD and 3 years of experience in EE/CE/CS or related fields.
- Strong understanding of energy consumption, power estimation, data movement, and low-power design.
- Familiarity with Verilog and ASIC design principles, and experience with power analysis tools (e.g., PowerArtist, PrimePower).
- Solid coding and automation skills, preferably in Python, Perl, and C++.
- Experience or strong interest in machine learning, reinforcement learning, and data analytics applied to EDA or system-level optimization.
- Interest or experience in building and using LLMs or foundation models as engineering copilots for EDA/power/architecture workflows.
- Excellent communication and collaboration skills.
- A desire to implement data-driven, AI-assisted decision-making in power architecture.
Benefits
- Equity
- Benefits