採用
必須スキル
Python
We are now looking for a Power Methodology and Analysis engineer.
NVIDIA prides ourselves in having energy efficient products. We believe that continuing to maintain our products' energy efficiency compared to competition is key to our continued success. Our team is responsible for researching, developing, and deploying methodologies to help NVIDIA's products become more energy efficient; and responsible for analyzing fullchip and unit-level power data, and driving ASIC teams to improve their units’ power efficiency. Key responsibilities include developing techniques to model, analyze, and reduce power consumption of NVIDIA GPUs. As a member of the Power Modeling, Methodology and Analysis Team, you will collaborate with Architects, Performance Engineers, Software Engineers, ASIC Design Engineers, and Physical Design teams to study and implement power analysis and reduction techniques for NVIDIA's next generation GPUs and Tegra SOCs. Your contributions will help us gain early insight into energy consumption of graphics and artificial intelligence workloads, and will allow us to influence architectural, design, and power management improvements.
What you'll be doing:
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Use internally developed tools and industry standard pre-silicon gate-level and RTL power analysis tools, to help improve product power efficiency.
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Develop and share best practices for performing pre-silicon power analysis, Enhance internal power tools and automate best practices
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Perform comparative power analysis, to spot trends and anomalies, that warrant more scrutiny.
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Interact with architects and RTL designers to help them interpret their power data and identify power bugs; drive them to implement fixes.
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Select and run a wide variety of workloads for power analysis, Collaborate with performance and architecture teams to validate performance of the workloads
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Prototype a new architectural feature in Verilog and analyze power.
What we need to see:
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MS with 1-3 years of experience or PhD in related fields.
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Basic understanding of concepts of energy consumption, estimation, and low power design.
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Familiarity with Verilog and ASIC design principles, including knowledge of logic cells.
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Good verbal/written English and interpersonal skills; much collaboration with design teams is expected.
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Strong coding skills, preferably in Python, C++.
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Ability to formulate and analyze algorithms, and comment on their time complexity and memory consumption.
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Desire to bring data-driven decision-making and analytics to improve our products.
Ways to stand out from the crowd:
- Familiar with the power tools/flow development is a big plus
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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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.
News
·
NaNw ago
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.
News
·
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.
News
·
NaNw ago


