Applied AI Engineer (EDA), Platform Architecture

Apple Inc

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Work type
On-site
Location
Austin, TX
Posted
2 days ago

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Similar $207k
$156k most similar roles pay here $256k

This listing doesn't post a salary. Most similar roles pay $168,262–$246,127.

Based on 240 similar postings.

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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 1798 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1459 roles with salary data.

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TL;DR · Applied AI Engineer (EDA), Platform Architecture

As an Applied AI Engineer in Apple’s Platform Architecture group, you will join a team dedicated to advancing pre-silicon validation processes for Apple hardware. Your role involves designing autonomous AI agents that automate error resolution and simulation parameter tuning, significantly reducing maintenance burdens for verification teams. You will develop AI-driven workflows using EDA tools like Logic Equivalence Checking and wave dumps to diagnose issues and explore design alternatives autonomously. Additionally, you will build and maintain infrastructure supporting continuous research and experimentation, track industry trends in machine learning and LLMs, and occasionally travel to collaborate with development groups. The ideal candidate has experience in applied AI or EDA/Silicon fields, proficiency in scripting languages such as Python and C/C++, and a strong background in software engineering and data-driven experimentation.

What you'll do

  • Design and deploy autonomous AI agents for reviewing design changes and resolving conflicts.
  • Develop AI-driven workflows to flag simulation performance issues and tune design parameters automatically.
  • Apply internal and external EDA tools to diagnose issues and explore design alternatives autonomously.
  • Build and maintain infrastructure supporting continuous research and experimentation in AI and EDA.
  • Conduct data-driven experiments to optimize AI harnesses and measure task completion efficiency.
  • Track emerging machine learning use cases for application in silicon design verification workflows.
  • Explore unfamiliar codebases and rapidly prototype automated solutions using cutting-edge techniques.

What we're looking for

  • Bachelor’s degree in Computer Science, Electrical Engineering, Machine Learning, or related field.
  • Experience building, deploying, and maintaining LLM-based applications or agentic workflows.
  • Entry-level familiarity with EDA tools or hardware verification concepts.
  • Hands-on experience with RTL design, simulation, or hardware emulation platforms.
  • Scripting and infrastructure development skills in Python, C/C++.
  • Familiarity with Verilog, SystemVerilog, and HDL testbenches for functional verification.

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