Soc Cad Eda Engineer

AMD AMD · Semiconductors · MARKHAM, Canada · Engineering

This role focuses on integrating AI capabilities into SoC CAD and EDA flows, specifically developing and deploying agentic AI systems for automating multi-step design and verification tasks, and applying ML models for optimization and predictive modeling within these workflows. It involves collaboration with EDA vendors and design teams to enhance design schedules and quality of results.

What you'd actually do

  1. Develop the methodologies and strategies to accelerate SoC design schedules
  2. Implement and maintain SoC physical design and analysis automation flows
  3. Develop and integrate end-to-end AI capabilities into CAD flows — including ML-based optimization, predictive modeling, and LLM-assisted automation.
  4. Build and deploy agentic AI systems that automate multi-step design and verification tasks.
  5. Partner with EDA vendors (Synopsys, Cadence) feature roadmaps, reference flows, best practices, and AI co-development opportunities.

Skills

Required

  • Strong silicon hardware design background
  • Software and scripting proficiency
  • Expert scripting skills in Python, TCL, and Perl in a Linux/Unix environment
  • Experience with Verilog, RTL, and UPF for multi-clock domain and low power designs

Nice to have

  • Strong experience in SoC physical design implementation across multiple SoC generations
  • Strong understanding of EDA tools from Synopsys and Cadence.
  • Demonstrated experience applying AI to CAD, EDA, or hardware design problems.
  • Experience building or working with LLM-based tools, agentic AI frameworks, or AI-assisted automation pipelines.
  • Familiarity with distributed and cloud compute environments for flow automation.
  • Excellent verbal and written communication skills.

What the JD emphasized

  • hands-on experience applying machine learning to CAD or EDA workflows
  • applying ML models to improve QoR
  • building LLM-assisted flows
  • designing agentic systems that reduce manual iteration
  • Demonstrated experience applying AI to CAD, EDA, or hardware design problems.
  • Experience building or working with LLM-based tools, agentic AI frameworks, or AI-assisted automation pipelines.

Other signals

  • AI-driven capabilities at every stage of the stack, from silicon to system
  • applying machine learning to CAD or EDA workflows
  • intersection of AI and CAD
  • applying ML models to improve QoR
  • building LLM-assisted flows
  • designing agentic systems that reduce manual iteration
  • Develop and integrate end-to-end AI capabilities into CAD flows
  • Build and deploy agentic AI systems that automate multi-step design and verification tasks
  • Experience building or working with LLM-based tools, agentic AI frameworks, or AI-assisted automation pipelines