Jobs
Benefits & Perks
•Equity
•Equity
Required Skills
Python
Machine Learning
Deep Learning
Scientific Computing
NVIDIA’s deep learning and HPC platforms have made a huge impact in various fields and are broadly used across leading academic institutions, start-ups, and industry, including the world’s largest Internet companies. We need passionate and creative people to help us on building a AI framework that will solve the toughest and most relevant problems of humanity and problems that are at the cutting edge of science & engineering: weather/climate challenges, product design, digital twins, molecular dynamics, novel materials, accelerated drug development, etc.
What you'll be doing:
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Collaborate with some of the brightest minds in a leading AI company to develop a leading Physics-AI framework, NVIDIA Physics Nemo, for our academic and industrial partners to construct digital twins and machine learning simulation surrogates for real world science and engineering problems
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Work with internal teams at Nvidia and external users to validate the product with industrial applications
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Stay up to date with the latest research and innovations in deep learning techniques, implement and experiment with new ideas to develop and enhance NVIDIA's deep learning technologies with focus on simulations
What we need to see:
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BS or MS degree (PhD preferred) in computer science, mathematics, computational science/engineering, or related technical field or equivalent experience
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5 yrs of relevant experience
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Strong Python programming skills. Familiarity with containers, numeric libraries, modular software design
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Good knowledge of state-of-the-art DNN architectures and machine learning techniques and algorithms (graph networks, diffusion models, reinforcement learning etc.) with experience in developing or using major deep learning frameworks (Py Torch, Tensorflow, JAX etc.)
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Experience in solving and using machine learning for real world problems involving scientific/engineering simulations (multi-physics applications in CFD, structural, thermal, electrical, electromagnetics, optics, acoustics etc. for various industries such as automotive, aerospace, machinery, medical, energy, computers, semiconductors, consumer goods etc.)
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Experience with scientific visualization is a big plus
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Strong analytical skills with bias for action
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Good time management and organization skills to thrive in a fast paced, dynamic environment
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Solid written and oral communications skills. Good teamwork and interpersonal skills
Ways to stand out from the crowd:
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Work with multi-node systems with data-parallel and model parallel programming experience
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Experience with CUDA. Usage of nonlinear simulation tools and techniques, usage of major simulation codes (opensource and/or commercial). Development and applications of the new architectures and algorithms on industry scale problems
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Published papers in the field of AI in scientific computing
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you! 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 deep learning — 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. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most thoughtful people in the world.
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 February 16, 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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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
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