招聘
Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car powered by AI can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error — this is truly an extraordinary time and the era of AI has begun. Image recognition and speech recognition — GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. The GPU started out as the engine for simulating human creativity, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and AI come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for Deep Learning, and NVIDIA is increasingly known as "the AI computing company." Make the choice to join us today.
Our team builds NVIDIA's end-to-end autonomous driving application. We are seeking software engineers, who want to work "full stack" on crafting self-driving solutions on NVIDIA's multi-computer and heterogeneous hardware architectures. We are now looking for a Senior Integration Engineer, Autonomous Vehicle.
What you’ll be doing:
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Defining functional software architecture NVIDIA's L2/L3/L4 autonomous driving solutions.
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Integrating modular software components (e.g. perception, planning, etc.) together to implement customer-required self-driving functions.
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Optimizing product implementation to achieve target performance goals.
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Diagnosing system software & functional driving issues reported on our target driving platforms, including on-road & simulation.
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Developing efficient mechanisms to improve utilization on computers with multiple heterogeneous hardware engines.
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Performing in-vehicle tests, collecting data and completing autonomous drive missions.
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Developing system tests, documentation of product functions, evaluating quality and proposing corrective actions.
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Developing highly efficient product code in C++, making use of high algorithmic parallelism offered by GPGPU programming (CUDA).
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Follow quality and safety standards such as defined by MISRA.
What we need to see:
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PhD with 1+ year, MS with 3+ years, or BS (or equivalent experience) with 5+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.
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Excellent C and C++ programming skills.
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Experience developing and debugging multithreaded/distributed applications like multimedia systems, game engines, etc.
Profound knowledge of programming and debugging techniques.
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Experience on developing software in heterogeneous architectures, including GPUs.
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Knowledge of image processing APIs (e.g. OpenCV) and MATLAB tools, automotive systems, notably ADAS applications.
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Software development for CUDA, Linux, and QNX.
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Experience with version control systems GIT and build system like CMake/Bazel.
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Be hands-on and work well within a team of algorithm, software and hardware engineers, with a significant level of detail orientation and a penchant for data organization and presentation.
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Solid understanding on Linux, Android, and/or other real-time operating systems.
Ways to stand out from the crowd:
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Understanding of parallel, embedded and distributed architectures.
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Thrive on writing low latency, highly performant code.
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Great communication and analytical skills.
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Self-motivated and a great teammate.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until March 21, 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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关于NVIDIA

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
员工数
Santa Clara
总部位置
$4.57T
企业估值
评价
4.1
10条评价
工作生活平衡
3.5
薪酬
4.2
企业文化
4.3
职业发展
4.5
管理层
4.0
75%
推荐给朋友
优点
Great culture and supportive environment
Smart colleagues and excellent people
Cutting-edge technology and learning opportunities
缺点
Team-dependent experience and outcomes
Work-life balance issues with long hours
Politics and influence over competence
薪资范围
73个数据点
Junior/L3
Mid/L4
Junior/L3 · Analyst
7份报告
$170,275
年薪总额
基本工资
$130,981
股票
-
奖金
-
$155,480
$234,166
面试经验
7次面试
难度
3.1
/ 5
体验
正面 0%
中性 86%
负面 14%
面试流程
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Interview
5
System Design Interview
6
Team Review
常见问题
Coding/Algorithm
System Design
Technical Knowledge
Behavioral/STAR
新闻动态
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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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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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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