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Validation Data Engineer, Verification and Validation - Autonomous Vehicles
China, Shanghai
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On-site
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Full-time
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1mo ago
必須スキル
Python
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
The Autonomous Vehicles Verification and Validation (AV V&V) team is hiring a Validation Data Engineer to build tooling, perform large‑scale analysis, and drive data‑driven evaluation of vehicle‑level behavior and Operational Design Domain (ODD) coverage during scaled testing. We are a core part of how NVIDIA scales and validates DRIVE AV software across regions, customers, and vehicle platforms, and we're looking for someone who is excited to help shape the future of safe autonomous driving!
What You’ll Be Doing:
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In this role, you will work on large‑scale driving behavior and ODD analysis using extensive real-world and virtual AV driving logs to evaluate safety, comfort, and overall vehicle-level performance.
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Implement and improve evaluation frameworks, data pipelines, and data curation strategies to support robust analysis across thousands of test miles every single day.
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Define and compute core metrics that quantify AV performance against target ODDs, powering our product development flywheel, technical reviews, and AV software releases.
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Contribute to scalable workflows that use cloud platforms, modern data engineering tools, and AI workflows to surface insights, spot regressions, and enable data‑driven decision making.
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Work closely with our Software Product, Testing and Development teams to turn open-ended safety and performance questions into clear quantitative analyses.
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Develop dashboards and reports that make sophisticated validation results easy to understand and act on for both engineering and senior leadership.
What We Need To See:
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MS or PhD in Computer Science, Mathematics, Statistics, Electrical/Computer Engineering, or a related quantitative field, or equivalent experience.
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5+ years of proven experience in data engineering or analytics roles working with large‑scale data; data science experience is a plus.
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Experience analyzing behavior of autonomous vehicles, ADAS systems, or other safety‑critical cyber‑physical systems.
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Strong Python skills, including writing production‑quality code and libraries for data processing, analysis, and automation.
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Hands‑on experience building and operating data pipelines in a production environment with cloud computing platforms.
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Excellent communication and teamwork skills, with a track record of working across teams and presenting your findings to technical collaborators.
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Ability to create clear dashboards, visualizations, and concise summaries for different audiences.
Ways To Stand Out From The Crowd:
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Background in statistics including experimental design, hypothesis testing, confidence intervals, and explaining results for non‑experts.
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Experience designing and scaling data and ML/AI pipelines to process and analyze very large telemetry or log datasets.
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Experience with GPU‑accelerated and/or distributed computing for large‑scale data processing and model evaluation.
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Familiarity with simulation‑based validation, vehicle‑level testing, and interpreting fleet test or on‑road validation data.
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Experience contributing to technical direction for a data or analytics team, such as helping define metrics, validation methods, or coding guidelines.
If you enjoy asking questions like “How do we know it’s safe enough?” and “What does the data really say?”, you’ll feel right at home here, and we’d love to hear from you! Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
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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
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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