Senior Applied AI and AI Infrastructure Engineer - Chip Design and DFX

at Nvidia

USD 200,000-379,500 per year

SENIOR

✅ On-site

Tech Stack
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1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

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AI @ 7 AWS @ 4 Azure @ 4 Communication @ 6 Data Modeling @ 4 Deep Learning Distributed Systems @ 6 ETL @ 4 GCP @ 4 GPU Machine Learning @ 7 Python @ 7 SQL @ 4

Details

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-X Engineering at NVIDIA works on groundbreaking innovations involving crafting creative solutions in AI for Chip Design and AI for Predictions in various use cases in manufacturing testing on some of the industry’s most complex semiconductor chips.

Responsibilities

As a senior member in our team, you will work on Applied AI projects that requires ML & Gen AI expertise.
You will work on building and managing deployment cycles as part of the AI Infrastructure requirements at an org-wide level.
For setting up a robust AI infrastructure, you will be the liaison between on-prem infrastructure teams and SW dev teams, while monitoring performance, automating deployments and maintaining code pipelines.
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.

Requirements

BSEE (or equivalent experience) with 12+ years, MSEE with 10+ years, or PhD with 6+ years of experience in AI Infrastructure management, Applied Machine Learning and Gen AI.
Excellent knowledge in building agents and multi-agentic ecosystems.
Experience with SQL, ETL, and data modeling.
Hands-on experience with cloud platforms (AWS, Azure, GCP).
Architect and optimize multi-region, globally distributed systems to meet our high standards for availability, latency, and throughput.
Lead data modeling, performance tuning, and capacity planning for large-scale mission-critical Gen AI workloads.
Strong programming skills in Python, C++ expected.
Outstanding written and oral communication skills with the curiosity to work on rare challenges.

Ways to stand out from the crowd

Experience in Ai infrastructure management for real-world systems.
Experience in application of AI for Chip Design 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.