Senior Timing CAD Engineer, Applied AI

Reposted 15 Hours Ago
Be an Early Applicant
2 Locations
In-Office
136K-213K Annually
Mid level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Develop AI-driven solutions for timing and constraint analysis, integrating data sources and automating workflows in semiconductor design. Collaborate with teams to enhance productivity and model validation.
Summary Generated by Built In

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 resolve, that only we can seek, and that matter to the world. This is our life’s work, to amplify human inventiveness and intelligence. NVIDIA’s ASIC-PD Methodology organization is driving the next generation of AI-assisted timing and constraint sign-off, integrating advanced analytics, orchestration frameworks, and domain-specific reasoning to accelerate design closure across multi-billion transistor chips.

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 3 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

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 136,000 USD - 212,750 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 18, 2025.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.

Top Skills

Agentic Ai Frameworks
Graph Neural Networks
Nanotime
Primetime
Python
PyTorch
Tempus
TensorFlow
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s 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 — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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