GenAI Physical Synthesis Engineer

Apple Inc

Quick summary

Work type
On-site
Location
Austin, TX
Posted
55 days ago
Nearby
99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $185k
$137k most similar roles pay here $234k

This listing doesn't post a salary. Most similar roles pay $153,100–$216,250.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1723 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1398 roles with salary data.

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At a glance

TL;DR · GenAI Physical Synthesis Engineer

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As a GenAI Physical Synthesis Engineer at Apple's Silicon Technologies group, you will lead the development of intelligent automation solutions that revolutionize RTL-to-GDS implementation flows. Your day-to-day responsibilities include designing and implementing AI-powered agents using Model Context Protocol (MCP) to optimize physical synthesis processes autonomously. You will collaborate with cross-functional teams to integrate these agentic solutions with industry-standard EDA tools like Fusion Compiler and Genus, enhancing their capabilities through seamless AI-driven workflows. This role requires expertise in GenAI frameworks, large language models, and scripting languages such as TCL, Python, or Perl for EDA tool automation. Ideal candidates also have experience with Python AI/ML libraries (PyTorch, TensorFlow), prompt engineering, and cloud platform deployment, making significant contributions to the cutting-edge field of AI-enhanced chip design at scale.

Skills

GenAI Python TCL MCP Fusion Compiler Genus PyTorch TensorFlow Transformers AutoGen CrewAI LangChain UPF Conformal LEC Formality Cloud platforms Docker CI/CD

What you'll do

  • Design and develop GenAI-powered agentic applications for physical synthesis optimization.
  • Implement intelligent agents using Model Context Protocol (MCP) to enhance synthesis flows.
  • Create AI-driven solutions that autonomously analyze and optimize Physical Synthesis workflows.
  • Build CAD tools leveraging GenAI for synthesis optimization and automated debugging.
  • Integrate agentic solutions with EDA tools like Fusion Compiler and Genus for seamless workflows.

What we're looking for

  • Experience with GenAI frameworks and large language models.
  • Proficiency in developing AI agents using Model Context Protocol (MCP).
  • Expertise in industry-standard synthesis tools like Fusion Compiler or Genus.
  • Strong scripting skills in TCL, Python, or Perl for EDA tool automation.
  • Understanding of physical synthesis concepts and CAD flows.
  • Experience with Python AI/ML libraries such as PyTorch, TensorFlow, and Transformers.

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