Quick Overview
Seniority
Leader
Employment type
Full Time
Work mode
Hybrid
Location
Austin, United States
Posted
8 months ago
Machine Learning
Job Description
For over four decades, Cirrus Logic has been propelled by the top engineers in mixed-signal processing. Our rockstar team thrives on solving complex challenges with innovative end-user solutions for the world's top consumer brands. Cirrus Logic is also known for its award-winning culture, which was built on a foundation of inclusion and fairness, meaningful community engagement, and delivering enjoyable employee experiences at every turn. But we couldn’t do it without our extraordinary workforce – and that’s where you come in. Join our team and help us continue to make Cirrus Logic an exceptional place to grow your career!
Are you a system-on-chip visionary, an architect who thrives at the frontier where hardware and machine learning meet? Do you want to shape the compute fabric that powers next-generation sensing, voice/image, and control at the edge? Cirrus Logic’s Technology Accelerator, Cirrus Venture Labs (CVL) may be the place for you.
CVL is a newly established incubator focused on developing disruptive, scalable, and monetizable innovations that solve high-impact industry problems. Our mission is to deliver foundational silicon technologies that redefine what’s possible for mixed-signal processing in new markets, accelerating Cirrus Logic’s diversification and strategic growth.
As a Principal SoC Architect (ML Accelerators), you will play a pivotal role in defining the architectures and design tradeoffs of ML-centric SoCs that fuse analog precision, digital signal processing, and embedded machine learning. Reporting to the Head of New Business and Technology Development, you will guide the design principles for custom accelerators, memory hierarchies, and SoC fabrics optimized for our target domains, Voice/Image, Sense, and Control. You will work alongside internal and external teams, startups, and academic partners to prototype breakthrough architectures, validate them in real-world scenarios, and chart the path to scalable silicon implementation.
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