Applied AI Engineer, Platform Architecture

Apple Inc

Confirmed live yesterday Trusted

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$129,300–$225,300 / yr
Posted
91 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $202k
This role $177k
$115k most similar roles pay here $264k

This role pays less than 67% of similar roles. Most pay $162,000–$241,750 — the shaded band above. At the midpoint, this role pays about $177k versus about $202k for comparable roles.

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 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

The Applied AI Engineer (EDA), Platform Architecture joins the Platform Architecture group to develop high-performance verification systems and tools for silicon development. This role focuses on building and deploying agentic AI workflows to automate pre-silicon validation processes, including triaging errors, tuning simulation parameters, and reducing maintenance burdens for verification teams. The engineer will design autonomous agents to review design changes, manage infrastructure, and conduct data-driven experiments to optimize prompt engineering and token efficiency. Key technical requirements include proficiency in Python or C/C++, experience with Large Language Models, and familiarity with EDA tools such as Logic Equivalence Checking, wave dumps, and design libraries. The role addresses the challenge of accelerating silicon verification by integrating advanced machine learning techniques into Electronic Design Automation workflows to automate complex hardware design tasks and optimize simulation performance.

What you'll do

  • Design and deploy autonomous AI agents to triage errors, resolve conflicts, and review design changes.
  • Develop AI-driven workflows to automatically tune design 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 prompts, 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 involving LLM-based applications, agentic workflows, and advanced prompt engineering.
  • Experience in EDA or Silicon including RTL design, simulation, or hardware emulation platforms.
  • Proficiency in scripting and software engineering using languages such as Python or C/C++.
  • Hands-on experience with Design Verification tasks and EDA tools like Logic Equivalence Checking and waveform debugging.
  • Familiarity with Verilog, SystemVerilog, or architecting HDL testbenches for functional verification.
  • Experience applying research methods including literature review and data-driven experimentation to solve hardware problems.

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