採用
必須スキル
Machine Learning
We are looking for a passionate team member to contribute to our autonomous driving product! The role involves applying deep learning and computer vision technologies to 3D/4D world modeling for autonomous vehicles. Our work is crucial to empower the training and testing of end-to-end driving models through end-to-end close-loop simulation. You will have the opportunity to work with a diverse team of researchers and engineers in the field of 3D/4D reconstruction, world modeling and simulation to deliver impact to our customers around the world!
What you’ll be doing:
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Build innovative world reconstruction systems using large geometry models, perception models, Gaussian splatting, diffusion models, and generative world models.
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Invent evaluation methods to measure the reconstruction and simulation quality.
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Develop tools to visualize and triage evaluation metrics.
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Build automated and agentic workflows to boost developer efficiency.
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Profile and optimize the performance of neural networks training and deployment.
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Relentlessly improve the reconstruction fidelity and simulation realism.
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Collaborate with scientists and developers across several organizations.
What we need to see:
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BS, MS, or PhD degree or equivalent experience in Engineering or Computer Science with a focus on Generative AI, Deep Learning, Computer Vision, Robotics, Computer Graphics, or a related field.
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5+ years Hands on experience with structure from motion, dense reconstruction, Gaussian splatting, diffusion models, and/or generative world models.
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Solid fundamentals in 3D computer vision and deep learning.
Ways to stand out from the crowd:
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Experience in autonomous driving: evidence of practical experiments and projects within the autonomous driving domain, showcasing your ability to apply machine learning algorithms to solve sophisticated problems in this field.
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Published research: particularly around Gaussian splatting, image/video diffusion models, or generative world models demonstrating a deep understanding and contribution to the field.
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, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
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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