NVIDIA has continuously reinvented itself over two decades. Our 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. 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. Make the choice to join us today.
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:
As a senior member in our team, you will work with pre-silicon and post-silicon data analytics - visualization, insights and modeling.
Design and uphold sturdy data pipelines and ETL processes for the ingestion and processing of DFX Engineering data from various origins
Lead engineering efforts by collaborating with cross-functional teams (execution, analytics, data science, product) to define data requirements and ensure data quality and consistency
You will work on hard-to-solve problems in the Design For Test space which will involve application of algorithm design, using statistical tools to analyze and interpret complex datasets and explorations using Applied AI methods.
In addition, you will help develop and deploy DFT methodologies for our next generation products using Gen AI solutions.
You will also help mentor junior engineers on test designs and trade-offs including cost and quality.
What we need to see:
BSEE (or equivalent experience) with 5+, MSEE with 3+, or PhD with 1+ years of experience in low-power DFT, Data Visualization, Applied Machine Learning or Database Management.
Experience with SQL, ETL, and data modeling is crucial
Hands-on experience with cloud platforms (AWS, Azure, GCP)
Design and implement highly scalable, fault tolerant distributed database solutions
Lead data modeling, performance tuning, and capacity planning for large-scale, mission-critical storage workloads
Excellent knowledge in using statistical tools for data analysis & insights.
Strong programming and scripting skills in Perl, Python, C++ or Tcl is expected
Outstanding written and oral communication skills with the curiosity to work on rare challenges.
Ways to stand out from the crowd:
Experience in data pipeline and database architecture for real-world systems
Experience in application of AI for EDA-related problem-solving
Good understanding of technology and passionate about what you do
Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic environment
NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most forward-thinking 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!
#LI-Hybrid
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 - 230,000 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.Skills Required
- BSEE with 5+, MSEE with 3+, or PhD with 1+ years of relevant experience (low-power DFT, Data Visualization, Applied Machine Learning or Database Management)
- Experience with SQL
- Experience with ETL processes
- Experience with data modeling
- Hands-on experience with cloud platforms (AWS, Azure, GCP)
- Design and implement highly scalable, fault tolerant distributed database solutions
- Lead data modeling, performance tuning, and capacity planning for large-scale storage workloads
- Excellent knowledge of statistical tools for data analysis and insights
- Strong programming and scripting skills in Perl, Python, C++ or Tcl
- Outstanding written and oral communication skills
- Experience in data pipeline and database architecture for real-world systems
- Experience applying AI to EDA-related problem solving
- Strong collaborative and interpersonal skills and ability to guide and influence in a dynamic environment
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
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. Today, NVIDIA is increasingly known as “the AI computing company.”
