NVIDIA
Semiconductor
AppliedAIEngineer-DFTMethodology
Neural analysis suggests this role is
optimal for Mid candidates.
“Applied AI Engineer - DFT Methodology at NVIDIA. Skills: Applied AI, Generative AI, LLMs, RAGs, Agentic AI, DFT, VLSI, Machine Learning. work on exploring Applied AI solutions for DFX and VLSI problem statements. Architect end-to-end generative AI solutions with a focus on LLMs, RAGs & Agentic AI workflows”
Industry & Context.
highly scalable and massively parallel computation horsepower that NVIDIA GPUs excel; hard to solve; only we can address; matter to the world; language-related engineering challenges; EDA-related problem-solving
What They're Looking For.
Must Have
BSEE or MSEE from reputed institutions with 2+ years of experience in DFT, VLSI & Applied Machine Learning, Experience in Applied ML solutions for chip design problems, Significant experience in deploying generative AI solutions for engineering use cases, Good understanding of fundamental DFT & VLSI concepts - ATPG, scan, RTL & clocks design, STA, place-n-route and power, programming and scripting skills in Perl, Python, C++ or TCL desired, organization and time management skills to work in a fast-pace multi-task environment, Self-motivated, independent, ability to work independently with minimal day-to-day direction, Outstanding written and oral communication skills with the curiosity to work on rare challenges
Nice to Have
Experience in application of AI for EDA-related problem-solving is a plus
What You'll Do.
work on exploring Applied AI solutions for DFX and VLSI problem statements
Architect end-to-end generative AI solutions with a focus on LLMs
RAGs & Agentic AI workflows
Work on deploying predictive ML models for efficient Silicon Lifecycle Management of NVIDIA's chips
Define how data will be collected
consumed and managed for next-generation AI use cases
help mentor junior engineers on test designs and trade-offs including cost and quality
How You'll Work.
Team & Collaboration
Collaborate closely with various VLSI & DFX teams to understand their language-related engineering challenges and design tailored solutions; Partner closely with cross-functional AI teams to provide feedback and contribute to the evolution of generative AI technologies; Work closely with DFX teams to integrate Agentic AI workflows into their applications and systems
Communication Scope
Outstanding written and oral communication skills
Full Job Description
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:** * As an integral member in our team, you will work on exploring Applied AI solutions for DFX and VLSI problem statements. * Architect end-to-end generative AI solutions with a focus on LLMs, RAGs & Agentic AI workflows. * Work on deploying predictive ML models for efficient Silicon Lifecycle Management of NVIDIA's chips. * Collaborate closely with various VLSI & DFX teams to understand their language-related engineering challenges and design tailored solutions. * Partner closely with cross-functional AI teams to provide feedback and contribute to the evolution of generative AI technologies. * 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. * Define how data will be collected, stored, consumed and managed for next-generation AI use cases. * You will also help mentor junior engineers o
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