Senior Design Automation Engineer, Applied AI

at Nvidia
USD 196,000-368,000 per year
SENIOR
✅ On-site

Used Tools & Technologies

Machine Learning LLM

Required Skills & Competences

Python @ 6 TensorFlow @ 6 Debugging @ 4 Experimentation @ 7 PyTorch @ 6 AI @ 4 Agentic AI @ 6 Data Pipelines @ 4 LangChain @ 6

Details

NVIDIA is 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.

Responsibilities

  • 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.
  • Own the end-to-end lifecycle: data curation, model training, deployment, monitoring, and continuous improvement in production environments.

Requirements

  • 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, and sign-off workflows.
  • Proficiency in Python, PyTorch/TensorFlow, and graph or agentic AI frameworks (examples given: 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, prompt-based reasoning, 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

  • 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.

Compensation & Other Details

  • 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 March 21, 2026.
  • NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.