채용
Benefits & Perks
•Equity
•Equity
Required Skills
C
Python
Deep Learning
PyTorch
TensorFlow
Linux
Git
Step into the future with NVIDIA, a global leader in AI computing, data science, and graphics, driving innovation in Artificial Intelligence, Deep Learning, and Autonomous Vehicles. Our team of visionaries is reshaping industries worldwide with cutting-edge technologies. Join us on an exhilarating journey as a Senior Software Engineer, where you'll fuse our ADAS software stack with OEM applications, witnessing your creations hit the road in real-time. You would have opportunity to bring cutting Edge AI Models to Futuristic Cars. NVIDIA is synonymous with innovation, boasting trailblazers who are shaping the world with their forward-thinking approaches. This is your chance to be part of a vibrant community that's redefining the technological landscape. Ready to shape the future of automotive technology with NVIDIA? Apply now to be part of a team that's revolutionizing the industry and driving innovation to new heights. Your potential awaits!
We're hiring a mid‑level Software Engineer to build production AI for autonomous vehicles. If you're passionate about deploying robust, high‑performance models that run on GPUs in real cars, we'd like to hear from you.
What you’ll be doing:
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Design, develop, and maintain C and Python software for perception, prediction, and planning in advanced driver‑assistance and autonomous driving systems.
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Train, fine‑tune, and iterate on deep learning models (vision, multimodal, and transformer‑based architectures) using large‑scale driving datasets, then optimize them for real‑time inference on NVIDIA GPUs.
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Work with multi‑sensor data — cameras, radar, lidar — and contribute to training pipelines, data quality workflows, and automated evaluation infrastructure.
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Debug and resolve performance bottlenecks, edge cases, and integration challenges in a complex, safety‑critical codebase.
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Collaborate with ML researchers, systems engineers, and automotive partners to bring features from research prototypes to production‑ready systems.
What we need to see:
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4–8 years of professional software engineering experience, ideally in AI, robotics, or automotive domains.
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Proficiency in C (modern C14/17 or later) and Python, with demonstrated experience writing clean, maintainable code.
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Hands‑on experience training deep learning models (Py Torch or Tensor Flow): designing experiments, tuning hyperparameters, working with large datasets, and debugging model behavior.
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Strong Linux development skills: building, debugging, profiling, version control (git), and working within CI/CD workflows.
Familiarity with one or more of: -
GPU programming and optimization (CUDA, TensorRT, cuDNN)
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Computer vision and perception (object detection, segmentation, multi‑object tracking)
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Robotics or autonomous systems (ROS, ADAS features, simulation environments)
Ways to stand out from the crowd:
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Experience with camera calibration, sensor fusion, or multi‑camera perception systems.
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Knowledge of model optimization and deployment: quantization (INT8, FP8, 4‑bit), TensorRT‑LLM, ONNX Runtime, or similar frameworks.
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Background in training infrastructure: distributed training, experiment tracking, dataset versioning, hyperparameter optimization.
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Understanding of software quality practices for safety‑critical systems (code review, unit testing, static analysis; automotive standards knowledge is a plus).
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Open‑source contributions or published work in AI, robotics, or GPU computing.
Work on challenging, real‑world problems where your code directly impacts vehicle safety and performance. Collaborate with a talented, multidisciplinary team of researchers, engineers, and automotive experts. Solve hard technical problems at the intersection of deep learning, real‑time systems, and production software engineering. If this opportunity aligns with your background and interests, please apply with your resume and a brief description of relevant projects (links to GitHub, publications, or technical write‑ups are welcome). We look forward to connecting with you.
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About NVIDIA

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
Employees
Santa Clara
Headquarters
$4.57T
Valuation
Reviews
4.1
10 reviews
Work Life Balance
3.5
Compensation
4.2
Culture
4.3
Career
4.5
Management
4.0
75%
Recommend to a Friend
Pros
Great culture and supportive environment
Smart colleagues and excellent people
Cutting-edge technology and learning opportunities
Cons
Team-dependent experience and outcomes
Work-life balance issues with long hours
Politics and influence over competence
Salary Ranges
47 data points
Junior/L3
Mid/L4
Junior/L3 · Analyst
7 reports
$170,275
total / year
Base
$130,981
Stock
-
Bonus
-
$155,480
$234,166
Interview Experience
7 interviews
Difficulty
3.1
/ 5
Experience
Positive 0%
Neutral 86%
Negative 14%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Interview
5
System Design Interview
6
Team Review
Common Questions
Coding/Algorithm
System Design
Technical Knowledge
Behavioral/STAR
News & Buzz
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 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
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