Analog Layout Automation Engineer
Apple - San Diego, United States of America
Posted Apr 20, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
- Not verified last checked Jun 13, 2026
- Salary
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- 401(k) match
- Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.
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Schedule
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- Weekend work
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Application
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Analog Layout Automation Engineer San Diego, United States of America Join Apple's Silicon Engineering Group (SEG) and be at the forefront of shaping the next generation of Apple's systems-on-chip (SOCs)! Our SOCs, featuring multi-billion transistors, are the heart of iconic devices like iPhones, iPads, and Macs. We're seeking a highly skilled Analog Layout Automation Engineer to contribute to the evolution of Analog/Mixed-Signal (AMS) circuits, covering SerDes, PLLs, and sensors, with a focus on automation and leveraging AI/ML techniques for improved design and efficiency. As an Analog Layout Automation Engineer, you'll convert design concepts into silicon by collaborating with circuit designers and using advanced, including AI-powered, CAD tools to create high-performance analog and mixed-signal layouts. You will review floor plans, analyze circuits, run verification suites, and resolve LVS/DRC/ERC issues to deliver next-generation SOCs. You'll also drive automation by developing scripts, improving workflows, and applying AI/ML for layout optimization, verification acceleration, advanced modeling, intelligent quality metrics, reduced manual effort, and data-driven design insights. Minimum Qualifications: BS degree in technical discipline with minimum 10 years of relevant experience. Preferred Qualifications: Experience designing analog and mixed-signal layouts in deep-submicron CMOS and FinFET technologies. Strong programming/scripting skills in SKILL, Perl, TCL, Shell, and/or Python, with emphasis on layout automation, productivity tooling, and data analysis. Solid understanding of supervised and self-supervised learning, convolutional neural networks (CNNs), and core training concepts such as loss functions, backpropagation, and optimization. Hands-on experience with PyTorch for model development and experimentation. Demonstrated ability to automate layout tasks, flows, and quality checks
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