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Machine Learning Hardware Architect

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Meta

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Location:
United States , Sunnyvale

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

212000.00 - 294000.00 USD / Year
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Job Description:

In this position you will work with Machine Learning Hardware Architects, Digital Designers, and Software engineers to develop custom Machine Learning Hardware accelerators for delivery into multiple SoCs. You will collaborate with a world-class group of researchers and architects to implement and contribute to the development and optimization of low power machine learning accelerators and state-of-the-art SoCs.

Job Responsibility:

  • Technical lead for ML Hardware engineers, driving design from Architecture through to Product for AR/VR optimized silicon
  • Lead designs to surpass state of the art for metrics such as compute, bandwidth and power consumption
  • Work across disciplines, brainstorm big ideas, work in new technology areas, juggle/coordinate multiple initiatives, drive a concept into a prototype and ultimately guide the transition into a high-volume consumer product
  • Travel both domestically and internationally

Requirements:

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 12+ years of experience as a Hardware Design Engineer or Silicon Architect for production silicon shipped in volume
  • Experience in Machine Learning IPs Silicon development
  • Experience in digital design µArchitecture, RTL coding
  • Experience with methods for partitioning a solution across hardware and software, evaluating trade-offs such as speed, performance, power, area
  • Results oriented, proactive with demonstrated creative & critical thinking

Nice to have:

  • Experience in deep learning algorithms and techniques, e.g., convolutional neural networks, transformers, LLMs
  • Experience with SoC Architecture and subsystem Integration
  • Knowledge of industry trends and disruptive technologies
  • Experience with Firmware, DSP coding and optimization
  • Knowledge of Physical Design and Low power implementation
  • Collaborate and/or lead in a team environment
  • Master/PhD degree in EE/CS or equivalent areas
What we offer:
  • bonus
  • equity
  • benefits

Additional Information:

Job Posted:
January 23, 2026

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