Nvidia Senior Timing CAD Engineer Applied AI 

United States, Texas 

321238538

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