Digital ASIC Designer and Systems Engineer

Palo Alto, California
Engineering/Research
Full Time
Fathom Computing is developing high-performance machine learning computers built to run both training and inference workflows for large-scale artificial neural networks (ANNs).  As computing is largely limited by data transfer Fathom’s approach combines the power of CMOS electronics with advantages of optical data movement for performance far beyond what electronics-only computers are capable of.

We’re seeking a digital ASIC designer with a strong first principles approach to IC design, and an interest in neural networks and ML hardware. You will collaborate closely with colleagues from other disciplines (e.g. optics) to lead design and implementation of novel optoelectronic hardware.

Your scope of ownership includes silicon architecture; IC design, implementation, and validation; and working with SW to build accurate simulations.

Areas of contribution

    • Drive the design and implementation of the electronic aspects of a novel, complex, high-performance, deeply-integrated computing system
    • Contribute to the development and stewardship of all aspects of the system such as power budgets, thermal solutions, chip-level, and system-level architecture.
    • Select outside vendors and work with them to implement and fabricate custom ICs

Requirements

    • BS/MS/PhD in EE or equivalent experience
    • Wide range of experience in digital ASIC design
    • Proficiency in Cadence or Synopsys simulation and modeling tools
    • Hands-on experience in prototype bring-up, debugging, and functional verification
    • Ability to perform comprehensive electronic system characterization
    • Strong project management, planning, and organizational skills
    • Excellent communication skills and ability to collaborate on complex cross-disciplinary systems
    • Drive to build something that hasn’t been built before

Preferred

    • Significant academic or work contributions (including but not limited to published papers, patents, industry, and personal projects)
    • Deep understanding of the underlying physics in current silicon electronics
    • Knowledge or experience in machine learning and computer architecture

You'll do well here if...

    • You enjoy thoughtful discussions fueled by problem-solving and logic
    • You're comfortable both leading and contributing individually
    • You're excited about the future of ML hardware
    • You enjoy teaching and learning from an interdisciplinary team


We highly encourage submission of a cover letter, just tell us why you're here :)