Applied AI Engineer, Platform Architecture

Apple Inc

Confirmed live yesterday Trusted

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Work type
On-site
Location
Austin, TX
Posted
91 days ago
Freshness
Confirmed live yesterday

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Similar $202k
$139k most similar roles pay here $262k

This listing doesn't post a salary. Most similar roles pay $162,000–$241,750.

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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 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · Applied AI Engineer, Platform Architecture

As part of the Platform Architecture group, the Applied AI Engineer (EDA), Platform Architecture will develop and deploy agentic AI workflows to automate and optimize pre-silicon validation processes. This role involves building autonomous agents to triage errors, resolve design conflicts, and automatically tune simulation parameters while reducing maintenance burdens for silicon verification teams. The engineer will build AI harnesses, scripts, and infrastructure to support continuous research, while conducting data-driven experiments to improve prompt efficiency and reduce hallucination rates. Key technical requirements include proficiency in Python or C/C++, experience with Large Language Models, and advanced prompt engineering. Candidates may also utilize EDA tools such as Logic Equivalence Checking, wave dumps, and design libraries. The work focuses on the intersection of hardware design and verification, specifically solving problems related to silicon design workflows and high-performance simulation solutions.

What you'll do

  • Design and deploy autonomous AI agents to triage errors and resolve design conflicts.
  • Develop AI-driven workflows to automatically tune simulation parameters and identify optimization candidates.
  • Integrate internal and external EDA tools to diagnose issues and explore design alternatives.
  • Build and maintain infrastructure, scripts, and harnesses to support continuous research and experimentation.
  • Conduct data-driven experiments to optimize prompt engineering, token efficiency, and hallucination rates.
  • Evaluate emerging machine learning and LLM use cases for application in silicon design workflows.

What we're looking for

  • Bachelor's degree in Computer Science, Electrical Engineering, Machine Learning, or a related field (or equivalent practical experience).
  • Master's degree in Computer Science, Electrical Engineering, or a related AI/Hardware field is preferred.
  • Experience in Applied AI including building LLM-based applications, agentic workflows, and advanced prompt engineering.
  • Experience in EDA/Silicon including RTL design, simulation, hardware emulation platforms, or applying ML to hardware problems.
  • Proficiency in scripting, infrastructure development, and software engineering using Python or C/C++.
  • 10+ years of relevant industry experience is preferred.
  • Hands-on experience with Design Verification tasks involving LEC, linting, waveform debugging, and simulation flows.
  • Familiarity with Verilog, SystemVerilog, or architecting HDL testbenches for functional verification.

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