Systems Software Developer (CAD Infrastructure)
Apple
Austin, TX • 20m ago • On-site
Senior
On-site
184,700 - 324,800 USD/yr
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Potential salary for Systems Software Developer (CAD Infrastructure) role
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$184,700 – $324,800/year
Quick Facts
Role: Systems Software Developer (CAD Infrastructure)
Focus: Post-silicon infrastructure, automated data pipelines, and end-to-end test program creation
Description
Help architect, develop, and support automated infrastructure and flows used by post-silicon teams for data management and data processing. Partner with Product and Test Engineering (PTE) to build a full pipeline for test program creation, reducing manual handoffs and accelerating the path from design intent to silicon on the tester. Join a CAD team supporting chip design efforts end to end.
Responsibilities
Architect, develop, and support post-silicon infrastructure systems (e.g., EMA, Memory Failure Analysis, Silicon Validation, Test Patterns, eFuses).
Build and maintain an end-to-end test program creation pipeline from test pattern management through finished test programs.
Lead large-scale infrastructure projects from specification through development and deployment.
Build and maintain databases, services, and automated pipelines for data extraction, validation, and signoff.
Monitor production flow health and drive resolution of complex issues.
Apply automation and AI-assisted tooling to reduce manual effort and improve reliability.
Promote these systems across Apple Silicon design teams; set and advocate software engineering standards and mentor other engineers.
Write documentation and provide training; collaborate with internal customers and cross-functional partners to continually improve workflows and systems.
Requirements
BS in Computer Science, Electrical or Computer Engineering, or a related field.
Experience with Python, Perl, or C++.
Experience working in Linux/Unix environments.
Benefits
Opportunity to define the architecture of an end-to-end silicon test flow used by engineers across new silicon bring-up.
Work on long-term infrastructure that shapes how chips are tested for years to come.
Apply modern automation and AI-assisted tooling to reduce manual effort and improve reliability.
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