Jobs
Required Skills
C
C++
Python
Deep Learning
TensorRT
CUDA
PyTorch
English
Mandarin
NVIDIA has continuously reinvented itself over two decades. NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. This is our life’s work — to amplify human imagination and intelligence.
AI becomes more and more important in self-driving car. NVIDIA is at the forefront of the AI-City and self-driving revolution and providing powerful solutions for them. All these solutions are based on GPU-accelerated libraries, such as CUDA and TensorRT, etc. Now, we are now looking for an GPU computing engineer based in Shanghai.
What you’ll be doing:
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Analyze Deep Learning models and investigate TensorRT stability and performance issues reported by customers or internal teams.
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Work with internationally distributed team with remote locations in US, APAC and India for CUDA and TensorRT developing.
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Extract the feature requirement or FAQ from the analysis and development and generate the documents.
What we need to see:
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Bachelor or equivalent experience of Computer Science or Electrical Engineering is required and Master Degree is preferred.
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3-5 years of related work.
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Strong programming skills in C and C and python.
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Have knowledge about the popular inference network and layers.
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Experience working with deep learning frameworks like Torch and Pytorch.
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Strong written and verbal communications in both English and Mandarin.
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Ability to work well in a diverse team environment as well as with cross site peers.
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Strong customer communication skills, powerfully motivated to provide highly responsive support as needed.
Ways to stand out from the crowd:
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Candidates is very good at Pytorch
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Strong customer communication skills, powerfully motivated to provide highly responsive support as needed.
#deeplearning
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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.
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
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