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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
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As an Applied AI Engineer (EDA), Platform Architecture, you will join the Platform Architecture group to develop and deploy agentic AI workflows that automate and optimize pre-silicon validation processes. You will build autonomous agents to triage errors, resolve conflicts, tune simulation parameters, and reduce maintenance burdens for silicon verification teams. Your daily work involves designing AI-driven workflows to flag performance concerns, building infrastructure for continuous experimentation, and optimizing prompts while measuring token efficiency and hallucination rates. The role requires proficiency in Python, C/C++, and experience with LLM-based applications or EDA tools like Logic Equivalence Checking, wave dumps, and design libraries. You will solve complex problems at the intersection of hardware design and verification by applying machine learning to automate tasks within the Electronic Design Automation domain to accelerate the development of high-performance silicon.
Design and deploy autonomous AI agents to review design changes, resolve conflicts, and triage simulation errors.
Develop AI-driven workflows to automatically tune design parameters and identify optimization candidates.
Integrate internal and external EDA tools to automate the diagnosis of hardware 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 Large Language Model 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 and maintaining LLM-based applications, agentic workflows, or advanced prompt engineering.
Experience in EDA/Silicon including RTL design, simulation, or hardware emulation platforms with a track record of applying software automation or ML to hardware problems.
Proficiency in scripting, infrastructure development, and software engineering using languages such as Python or C/C++.
Hands-on experience with Design Verification tasks involving LEC, linting tools, waveform debugging, and simulation 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.
Machine Learning
Generative AI
Python
C++
Deep Learning Frameworks
Time-series Analysis
SoC Architecture
Silicon
Feature Engineering
System Architecture