採用
Required Skills
Python
PyTorch
TensorFlow
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.
Here in the NVIDIA hardware accelerator team, we work on new architectures to support novel application areas and AI models. Our work includes researching the evolving landscape of AI applications and models, analyzing underlying model architectures, and building implementations for various NVIDIA hardware accelerators such as LPUs. We analyze mappings to existing and future accelerator systems, model performance, and work multi-functionally with the hardware design team on novel hardware features e.g. functional units, numeric modes, interconnect, system integration, etc. to unlock new application areas for NVIDIA accelerators. There are opportunities to participate in a wider range of R&D activities, either internally or externally with key NVIDIA partners.
What you’ll be doing:
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AI application and model research
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Performance modeling
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Multi-functional work with hardware and software teams
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Next generation hardware architecture development
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Support internal and outward-facing R&D
What we need to see:
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MSc or higher degree in CS/EE/CE/Mathematics or equivalent experience
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Minimum 2 years of relevant experience, preferably in AI models and applications
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Good foundation in computer science
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Knowledge of LLMs and other Gen AI applications
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Solid understanding of computer architecture and computer arithmetic
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Python and common ML frameworks such as Py Torch & Tensor Flow
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Experience with performance analysis / modelling
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Problem solving mentality
Ways to stand out from the crowd:
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Experience with scientific computing & HPC
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Prior experience in optimizing applications on specialized accelerators (GPU, FPGA, or other custom accelerators).
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Experience with compiler tools and MLIR.
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Experience in delivering complex projects in a fast paced environment.
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.
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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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
L3
L4
L5
L3 · Data Scientist IC2
0 reports
$177,542
total / year
Base
-
Stock
-
Bonus
-
$150,910
$204,174
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
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
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 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