Custom Analog Design Automation Lead

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Job Description:

Position Summary

Altera is seeking a Custom-Analog Design-Automation Lead to drive analog design automation and engineering productivity across the custom-analog design organization, with a strong emphasis on AI-assisted design flows. This role owns the strategy and execution for automating analog design tasks, embedding AI/ML-driven methodologies into the design cycle, and scaling productivity gains across multiple design teams.

Role Purpose

Lead analog design automation and productivity initiatives, including the development and deployment of AI-assisted design flows, to accelerate cycle time, improve quality of results, and reduce manual effort across custom-analog design programs.

Key Responsibilities

• Define and drive the technical strategy and roadmap for analog design automation and AI-assisted productivity tools.

• Develop, deploy, and maintain automation flows that span custom-analog design tasks, from schematic and layout through verification and signoff.

• Identify opportunities to apply AI/ML techniques to analog design problems (e.g., sizing, layout assistance, verification triage) and lead proof-of-concept through production deployment.

• Own the reuse and hardening strategy for analog IP and automation flows, ensuring methodologies are robust, well-documented, and portable across projects.

• Partner with design, CAD, and methodology teams to roll out automation and AI-assisted capabilities consistently across fabric, SerDes, and IO design groups.

• Establish metrics to track productivity, quality, and adoption of automation and AI-assisted flows, and report progress to engineering leadership.

• Mentor and provide technical direction to design and automation engineers adopting new flows and methodologies.

• Stay current with emerging EDA, automation, and AI/ML technologies relevant to custom-analog design, and evaluate them for adoption.

Scope

• Analog design automation spanning fabric, SerDes, and IO design domains.

• Reuse and hardening strategy for analog design IP, flows, and methodologies.

• Cross-team methodology deployment, influencing practices across multiple design groups rather than a single project.

Salary Range

The pay range below is for Bay Area California only. Actual salary may vary based on a number of factors including job location, job-related knowledge, skills, experiences, trainings, etc. We also offer incentive opportunities that reward employees based on individual and company performance.

$231,500 - $341,075 USD

We use artificial intelligence to screen, assess, or select applicants for the position. Applicants must be eligible for any required U.S. export authorizations.

Qualifications:

Minimum Qualifications

• Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, or a related field.
• 12+ years of experience in custom-analog circuit design and/or analog design automation, combined with hands-on experience in design automation and/or AI-assisted methodologies.

• Demonstrated ability to develop and deploy design automation methodology across multiple teams, not just within a single project.

• Working knowledge of analog/mixed-signal design flows (schematic capture, layout, extraction, verification) and the EDA toolchains that support them - Cadence Virtuoso Studio, Maestro/ADE, Spectre, Quantus QRC, Voltus-XFi/EMIR, Synopsys HSPICE/PrimeSim, or equivalent.

• Expert-level scripting and automation ability (Cadence SKILL, Python, Tcl, shell), sufficient to build and maintain production automation rather than extend what already exists.

• Demonstrated application of AI/ML to design or verification workflows, taken past proof-of-concept into production use by engineers other than the author.

• Direct experience working with foundry PDKs and EDA vendors to debug, characterize, and qualify tool behaviour at [CONFIRM NODES: e.g. Intel 18A / TSMC N3 / N5] and comparable advanced nodes.

• Strong communication and leadership skills, with the ability to influence design practices across fabric, SerDes, and IO teams.

Preferred Qualifications

• Prior experience leading a Center of Excellence (CoE) or cross-functional capability team.

• Experience with machine-learning-assisted EDA tools or building custom AI/ML tooling for circuit design tasks.

• Track record of IP reuse and hardening strategies that reduced design cycle time across multiple tapeouts.

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