Applied AI Engineer (EDA), Platform Architecture

Apple Inc.; Austin (TX); On-site; USD 100,000 - 130,000; Full time

Job summary

Apple Inc. seeks an Applied AI Engineer in Austin, Texas, focusing on AI automations, infrastructure development, and design verification.

The ideal applicant has a Bachelor's degree in Computer Science or Electrical Engineering and experience in applied AI or hardware verification. Responsibilities include designing AI agents and optimizing performance using advanced EDA tools.

Join a diverse team committed to inclusion and accessibility in the workplace.

Qualifications

• Bachelor’s degree in Computer Science or related field.
• Experience with applied AI or hardware verification.
• Strong scripting and software development skills.

Responsibilities

• Design and deploy autonomous AI agents.
• Develop AI-driven workflows for design.
• Apply EDA tools to evaluate design alternatives.
• Conduct data-driven experimentation to optimize designs.
• Track emerging machine learning use cases.

Skills

Applied AI

Hardware verification

Python

C/C++

EDA tools

Education

Bachelor's degree in Computer Science, Electrical Engineering, or related field

Master's degree in related AI/Hardware field

Tools

Logic Equivalence Checking

Waveform debugging

Verilog

SystemVerilog

Job description

Applied AI Engineer(EDA), Platform Architecture

Austin, Texas, United States Machine Learning and AI

Description

In this role, you will focus on AI based automations, infrastructure development, and continuous experimentation at the intersection of hardware design and verification.

Responsibilities

• Design and deploy autonomous AI agents to review design changes, resolve conflicts, and triage elaboration and simulation errors.
• Develop AI-driven workflows to flag simulation performance and design concerns, automatically tune design parameters, and explore optimization candidates autonomously.
• Apply internal and external EDA tools (e.g. Logic Equivalence Checking, wave dumps, design libraries) to automatically diagnose issues and explore design alternatives.
• Build and maintain AI harnesses, scripts, and infrastructure to support continuous research and experimentation.
• Conduct data-driven experimentation to optimize prompts and harnesses; measure and improve token efficiency, task completion, and hallucination rates.
• Track and evaluate emerging machine learning and Large Language Model (LLM) use cases in the broader industry for application in silicon design workflows.
• Occasionally travel (approximately once a year) to collaborate with development groups in the US.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Electrical Engineering, Machine Learning, or a related field (or equivalent practical experience).
• Experience in one of the following two areas: Applied AI (experience building, deploying, and maintaining LLM-based applications, agentic workflows, or advanced prompt engineering, combined with an entry-level familiarity with EDA tools or hardware verification concepts), or EDA/Silicon (experience with RTL design, simulation, or hardware emulation platforms, combined with a demonstrated track record of working in research-oriented roles applying software automation or ML to hardware problems).
• Experience with scripting, infrastructure development, and software engineering (e.g. Python, C/C++).

Preferred Qualifications

• Master’s in Computer Science, Electrical Engineering, or a related AI/Hardware field.
• Hands‑on experience with Design Verification tasks requiring application of EDA tools, including Logic Equivalence Checking (LEC), linting / static analysis tools, waveform debugging, and simulation / emulation flows.
• Familiarity with Verilog, SystemVerilog, or architecting HDL testbenches for functional verification.
• Experience developing software tools for co‑simulating designs across multiple high‑performance platforms.
• Comfortable exploring unfamiliar codebases, researching cutting‑edge techniques, and rapidly prototyping automated solutions.
• Experience applying research methods: literature review, data‑driven experimentation, analyzing results.
• Strong communication skills, with the ability to collaborate effectively with cross‑functional silicon engineering, design verification, and EDA development teams.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace

Learn about reasonable accommodations for job applicants

Apple accepts applications to this posting on an ongoing basis.