Job description

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. BS and a minimum of 10 years relevant industry experience. 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 using scripting and CAD tools. Proven record in implementing high-quality analog layouts with tight device matching, low noise, and low power consumption. Familiarity with failure-prone circuit/layout structures, analog and DFM best practices, and the ability to diagnose and resolve layout-related issues. Strong proficiency in custom and standard-cell floor planning, hierarchical layout assembly, and physical integration. Understanding of image processing fundamentals, spatial representations, multi-channel image handling, segmentation, and object detection concepts. Technical understanding of IR drop, RC delay, electromigration, self-heating, coupling capacitance, and related reliability concerns. High proficiency in interpreting physical verification reports, including DRC, ERC, and LVS. Experience using advanced Cadence Virtuoso features (XL, EAD, APR, Constraint Manager), and familiarity with Cadence Innovus. Experience with CAD automation workflows and PCell creation. Excellent communication skills and the ability to work effectively with cross-functional teams.

Requirements

Must-haves

BS and a minimum of 10 years relevant industry experience.
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 using scripting and CAD tools.
Proven record in implementing high-quality analog layouts with tight device matching, low noise, and low power consumption.
Familiarity with failure-prone circuit/layout structures, analog and DFM best practices, and the ability to diagnose and resolve layout-related issues.
Strong proficiency in custom and standard-cell floor planning, hierarchical layout assembly, and physical integration.
Understanding of image processing fundamentals, spatial representations, multi-channel image handling, segmentation, and object detection concepts.
Technical understanding of IR drop, RC delay, electromigration, self-heating, coupling capacitance, and related reliability concerns.
High proficiency in interpreting physical verification reports, including DRC, ERC, and LVS.
Experience using advanced Cadence Virtuoso features (XL, EAD, APR, Constraint Manager), and familiarity with Cadence Innovus.
Experience with CAD automation workflows and PCell creation.
Excellent communication skills and the ability to work effectively with cross-functional teams.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlpython

Platform: apple
Effort: medium