Senior DFT Methodology - Data Analytics and Applied AI Engineer

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