Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are seeking an Applied AI Engineer to lead end-to-end solution development — spanning data generation, model training, orchestration, and agentic automation — for timing and constraint analysis workflows. You will be part of a cross-disciplinary team building intelligent systems that learn from sign-off data, reason across flows, and assist engineers in achieving faster and more predictable closure. What You’ll be Doing: • Architect and develop AI-driven solutions for static timing, constraints quality, and closure prediction. • Integrate heterogeneous data sources — timing reports, constraint graphs, design metadata, silicon correlation — into structured knowledge bases and training pipelines. • Develop autonomous analysis agents that interact with timing tools (e.g., PrimeTime, Nanotime, Tempus) to perform multi-corner, multi-mode optimization and constraint debugging. • Implement scalable orchestration across Flow-Server and Digital Engineer platforms, enabling AI-in-loop decision-making for sign-off readiness. • Collaborate with methodology and sign-off teams to validate models on live projects, improving coverage, predictability, and engineering productivity. • Build interpretable AI pipelines using graph neural networks, large language models, and process-aware reasoning engines for timing closure recommendations. • Be responsible for the end-to-end lifecycle — from data curation and model training to deployment, monitoring, and continuous improvement in production environments. What We Need to See: • BS (or equivalent experience) in Electrical or Computer Engineering with 12+ years of experience in AI/ML solution development, ideally for EDA, semiconductor, or complex data domains • Strong background in VLSI/ASIC design — with deep understanding of timing, constraints, STA, or sign-off workflows. • Proficiency in Python, PyTorch/TensorFlow, and graph or agentic AI frameworks (e.g., LangGraph, LangChain, Ray, NetworkX). • Experience developing data pipelines, knowledge graphs, or process models for structured engineering data. • Working knowledge of timing tools (PrimeTime, Nanotime, Tempus) and scripting integration with EDA environments. • Experience with AI orchestration frameworks, reasoning based on prompts, and multi-agent automation is highly desirable. • Strong problem-solving skills, technical depth, and a mentality for experimentation and continuous learning. Ways to stand out from the crowd: • Experience with constraint validation, false-path detection, and timing-exception modeling. • Prior exposure to AI in physical design automation, Silicon/process modeling, or EDA flow automation. • Contributions to open-source AI or flow automation projects. • Publications or patents in AI for design automation or semiconductor engineering Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 196,000 USD - 310,500 USD for Level 5, and 232,000 USD - 368,000 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 4, 2026. 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.

Requirements

Must-haves

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.
Architect and develop AI-driven solutions for static timing, constraints quality, and closure prediction.
Integrate heterogeneous data sources — timing reports, constraint graphs, design metadata, silicon correlation — into structured knowledge bases and training pipelines.
Develop autonomous analysis agents that interact with timing tools (e.g., PrimeTime, Nanotime, Tempus) to perform multi-corner, multi-mode optimization and constraint debugging.
Implement scalable orchestration across Flow-Server and Digital Engineer platforms, enabling AI-in-loop decision-making for sign-off readiness.
Collaborate with methodology and sign-off teams to validate models on live projects, improving coverage, predictability, and engineering productivity.
Build interpretable AI pipelines using graph neural networks, large language models, and process-aware reasoning engines for timing closure recommendations.
Be responsible for the end-to-end lifecycle — from data curation and model training to deployment, monitoring, and continuous improvement in production environments.
BS (or equivalent experience) in Electrical or Computer Engineering with 12+ years of experience in AI/ML solution development, ideally for EDA, semiconductor, or complex data domains
Strong background in VLSI/ASIC design — with deep understanding of timing, constraints, STA, or sign-off workflows.
Proficiency in Python, PyTorch/TensorFlow, and graph or agentic AI frameworks (e.g., LangGraph, LangChain, Ray, NetworkX).
Experience developing data pipelines, knowledge graphs, or process models for structured engineering data.
Working knowledge of timing tools (PrimeTime, Nanotime, Tempus) and scripting integration with EDA environments.
Experience with AI orchestration frameworks, reasoning based on prompts, and multi-agent automation is highly desirable.
Strong problem-solving skills, technical depth, and a mentality for experimentation and continuous learning.
Experience with constraint validation, false-path detection, and timing-exception modeling.
Prior exposure to AI in physical design automation, Silicon/process modeling, or EDA flow automation.
Contributions to open-source AI or flow automation projects.
Publications or patents in AI for design automation or semiconductor engineering
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until July 4, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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Platform: eightfold
Effort: medium

Benefits

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Vision