
Pioneering accelerated computing and AI
Applied AI Engineer - DFT Methodology at NVIDIA
About the role
NVIDIA has continuously reinvented itself. Our invention of the GPU sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. Today, research in artificial intelligence is booming worldwide, which calls for highly scalable and massively parallel computation horsepower that NVIDIA GPUs excel.
NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world. This is our life’s work , to amplify human creativity and intelligence. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join our diverse team and see how you can make a lasting impact on the world! Design-for-Test Engineering at NVIDIA works on groundbreaking innovations involving crafting creative solutions for DFT architecture, verification, and post-silicon validation on some of the industry's most complex semiconductor chips.
What you'll be doing:
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As an integral member in our team, you will work on exploring Applied AI solutions for DFX and VLSI problem statements.
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Architect end-to-end generative AI solutions with a focus on LLMs, RAGs & Agentic AI workflows.
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Work on deploying predictive ML models for efficient Silicon Lifecycle Management of NVIDIA's chips.
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Collaborate closely with various VLSI & DFX teams to understand their language-related engineering challenges and design tailored solutions.
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Partner closely with cross-functional AI teams to provide feedback and contribute to the evolution of generative AI technologies.
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Work closely with DFX teams to integrate Agentic AI workflows into their applications and systems and stay abreast of the latest developments in language models and generative AI technologies.
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Define how data will be collected, stored, consumed and managed for next-generation AI use cases.
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You will also help mentor junior engineers on test designs and trade-offs including cost and quality.
What we need to see:
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BSEE or MSEE from reputed institutions with 2+ years of experience in DFT, VLSI & Applied Machine Learning
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Experience in Applied ML solutions for chip design problems
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Significant experience in deploying generative AI solutions for engineering use cases
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Good understanding of fundamental DFT & VLSI concepts
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ATPG, scan, RTL & clocks design, STA, place-n-route and power
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Experience in application of AI for EDA-related problem-solving is a plus
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Excellent knowledge in using statistical tools for data analysis & insights
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Strong programming and scripting skills in Perl, Python, C++ or TCL desired
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Strong organization and time management skills to work in a fast-pace multi-task environment
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Self-motivated, independent, ability to work independently with minimal day-to-day direction
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Outstanding written and oral communication skills with the curiosity to work on rare challenges
NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most brilliant and talented people in the world working for us and, due to unprecedented growth, our world-class engineering teams are growing fast. If you're a creative and autonomous engineer with real passion for technology, we want to hear from you!
Required skills
Applied AI
LLMs
RAG
Agentic AI
Machine learning
VLSI collaboration
Solution architecture
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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
10 reviews
4.4
10 reviews
Work-life balance
2.8
Compensation
4.5
Culture
4.2
Career
4.3
Management
3.8
78%
Recommend to a friend
Pros
Cutting-edge technology and innovation
Excellent compensation and benefits
Great team culture and collaboration
Cons
High pressure and expectations
Poor work-life balance and long hours
Fast-paced environment leading to burnout
Salary Ranges
79 data points
L3
L4
L5
L3 · Data Scientist IC2
0 reports
$177,542
total per year
Base
-
Stock
-
Bonus
-
$150,910
$204,174
Interview experience
5 interviews
Difficulty
3.0
/ 5
Interview process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
Common questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
Latest updates
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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