Senior SoC Functional Modeling Engineer, AWS Machine Learning Accelerators - Amazon : Job Details

Senior SoC Functional Modeling Engineer, AWS Machine Learning Accelerators

Amazon

Job Location : New York,NY, USA

Posted on : 2025-08-05T01:18:19Z

Job Description :
Senior SoC Functional Modeling Engineer, AWS Machine Learning Accelerators

Custom SoCs (System on Chips) are the brains behind AWS's Machine Learning servers. Our team builds C++ & SystemC functional models of these custom-designed accelerator SoCs for use by AWS internal teams. We're looking for a Senior SoC Modeling Engineer to join the team and deliver new functional models, infrastructure, and tooling for our customers.

As part of the ML accelerator modeling team, you will:

  • Develop and own SoC functional models end-to-end, including model architecture, integration with other model or infrastructure components, testing, and debug.
  • Work closely with architecture, RTL design, design verification, emulation, and software teams to build, debug, and deploy your models.
  • Innovate on the tooling you provide to customers, making it easier for them to use our SoC models.
  • Drive model and modeling infrastructure performance improvements to help our models scale.
  • Develop software which can be maintained, improved upon, documented, tested, and reused.

    • You will thrive in this role if you:

  • Are an expert in functional modeling for SoCs, ASICs, TPUs, GPUs, or CPUs.
  • Are comfortable modeling in C++ or SystemC, and familiar with Python.
  • Enjoy learning new technologies, building software at scale, moving fast, and working closely with colleagues as part of a small team within a large organization.
  • Want to jump into an ML-aligned role, or get deeper into the details of ML at the hardware/system-level.

    • Although we are building machine learning chips, no machine learning background is needed for this role. This role spans modeling of the ML and management regions of our chips, and you'll dip your toes into both. You'll be able to ramp up on ML as part of this role, and any ML knowledge that's required can be learned on-the-job.

    This role can be based in either Cupertino, CA or Austin, TX. The broader team is split between the two sites, with a slight preference for CA, due to colocation with more customer teams.

    A day in the lifeA few videos help explain what the Annapurna Labs ML team is working on:

  • Video 1
  • Video 2

    • About the teamAWS Utility Computing (UC) provides product innovations that continue to set AWS's services and features apart in the industry. As a member of the UC organization, you'll support the development and management of Compute, Database, Storage, Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.

    Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.

    BASIC QUALIFICATIONS
  • 6+ years of non-internship professional experience writing functional or performance models.
  • Experience programming with C++ and/or SystemC.
  • Familiarity with SoC, CPU, GPU, and/or ASIC architecture and micro-architecture.
    • PREFERRED QUALIFICATIONS
  • 6+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, and testing.
  • Experience developing and calibrating performance models for custom silicon chips.
  • Experience with writing benchmarks and analyzing performance.
  • Experience with PyTest and GoogleTest.
  • Familiarity with modern C++ (11, 14, etc.).
  • Experience in multi-threaded programming, vector extensions, HPC, and QEMU.
  • Experience with machine learning accelerator hardware and/or software.

    • Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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