Applied AI Engineer (EDA), Platform Architecture

Apple Inc

Quick summary

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

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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.

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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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At a glance

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

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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 primary responsibilities include designing autonomous AI agents that automate error triage and simulation parameter tuning, developing AI-driven workflows to optimize design verification, and applying EDA tools like Logic Equivalence Checking to diagnose issues. You will also build infrastructure to support continuous research and experimentation, focusing on improving token efficiency and reducing hallucination rates in AI systems. This role requires expertise in Python, C/C++, and a strong background in either applied AI or Electronic Design Automation (EDA), with experience in scripting, software engineering, and data-driven experimentation. The ideal candidate will have hands-on experience with EDA tools and be comfortable working on cutting-edge hardware verification challenges at scale.

Skills

Python C/C++ LLM-based applications EDA tools Logic Equivalence Checking Verilog SystemVerilog HDL testbenches CI/CD Prometheus Grafana

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 and deploying AI applications or working with EDA tools for hardware verification.
  • Proficiency in scripting languages like Python and software engineering practices.
  • Familiarity with Verilog, SystemVerilog, and HDL testbenches for functional verification.
  • Hands-on experience with Design Verification tasks using EDA tools such as LEC and simulation flows.
  • Ability to conduct data-driven experimentation and analyze results effectively.

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