Physical Design Engineer, Machine Learning

Summary

Come help us design the next generation of revolutionary Apple products. We are looking for an engineer who combines deep physical design expertise with hands-on machine learning skills. In this role, you will work on our physical design machine learning efforts — building predictive models, optimization algorithms, and autonomous agents that collaborate with our internal design teams to help our SOCs achieve optimal Power, Performance, and Area (PPA).

Description

As a member of the Physical Design Machine Learning team, you will help build the most efficient application processors on the planet, powering the next generation of Apple products. Job responsibilities include:

• Applying machine learning and advanced algorithms to solve hard, high-impact problems across the physical design flow: RTL and logic synthesis, floorplanning, place and route, timing/noise/power/thermal analysis, voltage drop, and design for manufacturing/yield
• Training and deploying models directly into production P&R flows to predict and optimize outcomes and speed up convergence
• Building tools and models designed to be used by agentic systems, as well as agents themselves, including autonomous or semi-assisted optimization loops that propose, evaluate, and iterate on design changes through EDA tooling
• Working across the full spectrum of ML techniques, from traditional models and classical optimization to GNNs, reinforcement learning, and LLM-based agents
• Collaborating cross-functionally with design, power, post-silicon, CAD, software, and machine learning teams in an engaging and rewarding environment

Minimum Qualifications

Minimum BS and 3+ years of relevant industry experience
Experience with optimization algorithms and programming in Python or C/C++
Academic or industry experience in physical design

Preferred Qualifications

Practical experience with a range of ML approaches including classical/traditional models, GNNs, transformers, diffusion models, and/or reinforcement learning
Experience building agentic systems, LLM-based agents, tool-calling/function-calling, multi-agent orchestration, or autonomous decision-making loops
Experience integrating ML models or agents into EDA tool flows via scripting (Python/TCL) or APIs
Master's or PhD with relevant publications in Machine Learning and/or EDA algorithms
Excellent communication and organizational skills

Pay & Benefits — San Jose, California, United States

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $150,400 and $277,600, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Application Deadline

Apple accepts applications to this posting on an ongoing basis.