Senior Design Automation Engineer, Applied AI

Nvidia

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Santa Clara, CAAustin, TX
Employment
Full-time
Posted
119 days ago
Freshness
Confirmed live yesterday

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Similar $192k
$132k $240k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $154,625–$230,000.

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About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Senior Design Automation Engineer, Applied AI

The Senior Design Automation Engineer, Applied AI will join a cross-disciplinary team to lead end-to-end solution development for timing and constraint analysis workflows. The role involves architecting AI-driven solutions for static timing, constraints quality, and closure prediction. Key responsibilities include integrating heterogeneous data sources into training pipelines, developing autonomous analysis agents, and implementing scalable orchestration across Flow-Server and Digital Engineer platforms. The engineer will build interpretable AI pipelines using graph neural networks, large language models, and process-aware reasoning engines. Required technical skills include proficiency in Python, PyTorch/TensorFlow, and agentic AI frameworks like LangGraph, LangChain, Ray, and NetworkX. The position addresses the technical challenge of improving engineering productivity and predictability in VLSI/ASIC design through automated sign-off readiness and multi-corner optimization.

What you'll do

  • Architect and develop AI-driven solutions for static timing, constraints quality, and closure prediction.
  • Integrate heterogeneous data sources into structured knowledge bases and training pipelines.
  • Develop autonomous analysis agents to interact with timing tools for multi-corner optimization and debugging.
  • Implement scalable orchestration across platforms to enable AI-in-loop decision-making for sign-off readiness.
  • Build interpretable AI pipelines using graph neural networks, large language models, and reasoning engines.
  • Manage the end-to-end lifecycle from data curation and model training to production deployment and monitoring.
  • Validate models on live projects to improve coverage, predictability, and engineering productivity.

What we're looking for

  • BS or equivalent experience in Electrical or Computer Engineering.
  • 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.
  • 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 (preferred).
  • Experience with constraint validation, false-path detection, or AI in physical design automation (preferred).

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