Applied AI Engineer, Silicon Co-Design Group, New College Grad 2026

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 tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Make the choice, join our diverse team today!

Working at the Silicon Co-design Engineering Team at NVIDIA, you will be responsible for productizing NVIDIA's chips into groundbreaking consumer, professional, server, mobile, and automotive solutions. The qualified candidate should be comfortable in a lab environment and should demonstrate a passion towards creation, execution and improvement of silicon validation plans.

What you’ll be doing:

• Build and deploy AI/ML + GenAI solutions (LLMs, classical ML) to accelerate silicon co-design and validation workflows.
• Develop AI assistants and agentic systems for SCG engineers using RAG, tool-calling, and fine-tuned models.
• Create scalable data + MLOps pipelines to collect/curate chip design & validation data and support training, evaluation, and production deployment.
• Partner with cross-functional silicon teams to identify high-impact automation opportunities, integrate solutions into existing flows, and drive measurable improvements in turnaround time and quality.
• Prototype and apply modern ML techniques relevant to silicon co-design  and share learnings via tech talks/knowledge sharing.

What we need to see:

• M.S. or Ph.D. (or completing within 6 months) in CS/EE/CE or related field or equivalent experience.
• Programming: Strong Python; plus C/C++ and/or Tcl/Perl/Bash.
• ML Foundation: Understanding of model development and evaluation; familiarity with Transformers/LLMs and at least one of CNN/RNN/GNN concepts.
• Frameworks: Hands-on with ML framework PyTorch / TensorFlow.
• Software Engineering: Strong fundamentals in Git, code reviews, testing, CI/CD, documentation.
• Skills: Strong debugging/problem-solving, ability to handle ambiguity, and effective communication/collaboration across HW/SW teams.
• Motivation: Interest in applying AI to semiconductor co-design/validation problems and learning the domain quickly.

Ways to stand out from the crowd:

• Familiarity with statistical methods, tools for data analysis, and analyzing large datasets to draw actionable conclusions, possibly applying deep learning techniques.
• Knowledgeable in signal integrity, timing analysis, fault analysis, sampling, computer architecture, filters.
• Familiar with lab tools (oscilloscopes and logic analyzers).
• Experience in Database and Web Development is a plus!

With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We welcome you join our team with some of the most hard-working people in the world working together to promote rapid growth. Are you passionate about becoming a part of a best-in-class team supporting the latest in GPU and AI technology? If so, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 100,000 USD - 166,750 USD for Level 1, and 116,000 USD - 189,750 USD for Level 2.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 27, 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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