採用
必須スキル
Python
Machine Learning
We’re looking for a Senior Power Architecture & Optimization Engineer to push the limits of energy efficiency using advanced analytics and AI, including LLMs trained specifically for power analysis.
NVIDIA’s leadership in accelerated computing depends on building the most energy‑efficient GPUs and So Cs in the industry. As AI and graphics workloads scale explosively, we believe that Power Analysis and Optimization driven by AI and LLMs is the future—and a key differentiator for our next generations of GPUs and Tegra So Cs. In this role, you’ll be at the center of that effort—combining power architecture expertise with machine learning, reinforcement learning, data analytics, and large language models (LLMs) to invent new ways to model, analyze, and optimize energy consumption across full‑chip and unit‑level designs.
What You’ll Be Doing:
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Analyze full‑chip and unit‑level power using internal and industry‑standard RTL and gate‑level power tools, and translate data into concrete design and architectural improvements.
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Develop and productionize power‑aware models and flows, including ML/RL‑based techniques for anomaly detection, dynamic power management, and design‑space exploration.
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Design and train new LLMs that “learn the art” of power analysis from design data, power reports, bug histories, and best practices—so they can:
Assist engineers in interpreting complex power data
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Propose likely root causes and candidate fixes
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Recommend architectural and micro‑architectural optimizations for power
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Perform comparative power analysis across workloads, products, and design options to identify trends, anomalies, and optimization opportunities that aren’t obvious from first principles alone.
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Partner closely with Architects, Performance, Software, ASIC Design, and Physical Design teams to interpret power data, root‑cause power bugs, and drive fixes and design changes.
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Prototype and evaluate new architectural features in Verilog, with a strong focus on their power and energy implications.
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Automate and scale flows (Python/Perl/C++), and define new pipelines that fast‑track power anomaly detection and close the loop between power data, AI models, and design decisions.
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Apply AI to power optimization: build and deploy data‑driven models—using machine learning, reinforcement learning, data analytics, and custom LLMs—to recommend or automatically tune power‑efficient configurations and policies.
What We Need To See:
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MS (or equivalent experience) and 5yrs experience OR PHD + 3yr experience in EE/CE/CS or related fields.
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Strong understanding of energy consumption, power estimation, data movement, and low‑power design.
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Familiarity with Verilog and ASIC design principles, and hands‑on experience with tools such as Power Artist, Prime Power/Prime Power RTL, RTL Architect, or similar.
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Solid coding and automation skills, preferably in Python, Perl, and C++.
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Experience or strong interest in machine learning, reinforcement learning, and data analytics, ideally applied to EDA, architecture, or system‑level optimization.
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Interest or experience in building and using LLMs or other foundation models as engineering copilots—especially for EDA/power/architecture workflows.
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Excellent communication and collaboration skills to work effectively with cross‑functional design and architecture teams.
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A genuine desire to bring data‑driven, AI‑assisted decision‑making into power architecture and help shape the energy profile of NVIDIA’s future products.
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 March 26, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.
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NVIDIAについて

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
従業員数
Santa Clara
本社所在地
$4.57T
企業価値
レビュー
4.1
10件のレビュー
ワークライフバランス
3.5
報酬
4.2
企業文化
4.3
キャリア
4.5
経営陣
4.0
75%
友人に勧める
良い点
Great culture and supportive environment
Smart colleagues and excellent people
Cutting-edge technology and learning opportunities
改善点
Team-dependent experience and outcomes
Work-life balance issues with long hours
Politics and influence over competence
給与レンジ
73件のデータ
Junior/L3
Mid/L4
Junior/L3 · Analyst
7件のレポート
$170,275
年収総額
基本給
$130,981
ストック
-
ボーナス
-
$155,480
$234,166
面接体験
7件の面接
難易度
3.1
/ 5
体験
ポジティブ 0%
普通 86%
ネガティブ 14%
面接プロセス
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Interview
5
System Design Interview
6
Team Review
よくある質問
Coding/Algorithm
System Design
Technical Knowledge
Behavioral/STAR
ニュース&話題
Negotiating NVIDIA's Offer
Base, stock, and sign-on negotiable. Recruiters invested in closing candidates. CEO reviews all 42K employee salaries monthly. Stock growth has made many employees millionaires.
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NVIDIA Company Reviews
WLB rated 3.9/5 (lowest category). 64% satisfied with WLB but 53% feel burnt out. Compensation rated 4.4-4.5/5. Experience highly team-dependent.
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NaNw ago
NVIDIA Interview Discussions
Technical bar is high with 4-6 rounds. Process takes 4-8 weeks. Expect C++ questions, LeetCode medium, and system design. Difficulty rated 3.16/5.
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NaNw ago
NVIDIA Culture Discussions
Team-dependent experience; sink-or-swim culture that rewards high performers but can be overwhelming. No politics, flat structure, but demanding workload with some teams requiring evening/weekend work.
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NaNw ago