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Description

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 to significantly left-shift development. We’re looking for a Senior SoC Virtual Platform 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 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

Annapurna Labs, our organization within AWS, designs and deploys some of the largest custom silicon in the world, with many subsystems that must all be modeled and tested with high quality. Our SoC model is a critical piece of software used in both our SoC development process and by our partner software teams as a virtual platform. You’ll collaborate with many internal customers who depend on your models to be effective themselves, and you'll work closely with these teams to push the boundaries of how we're using modeling to build successful products.

You will thrive in this role if you:

- Are an expert in modeling 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.

We're changing an industry. We're searching for individuals who are ready for this challenge, who want to reach beyond what is possible today. Come join us and build the future of machine learning!

Basic Qualifications

- 5+ years of non-internship professional software development experience

- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

- Experience as a mentor, tech lead or leading an engineering team

- 7+ years of non-internship professional experience writing functional or performance models

- Experience programming with C++ and/or SystemC

- Knowledge of SoC, CPU, GPU, and/or ASIC architecture and micro-architecture

Preferred Qualifications

- Bachelor's degree in computer science or equivalent

- Experience analyzing data and applying best practices to assess performance drivers

- Experience developing models that integrate with QEMU

- Experience developing and calibrating performance models for custom silicon chips

- Experience with PyTest and GoogleTest

- Familiarity with modern C++ (11, 14, etc.)

- Experience in multi-threaded programming

- Experience with machine learning accelerator hardware and/or software

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits .

USA, CA, Cupertino - 193,300.00 - 261,500.00 USD annually

USA, TX, Austin - 168,100.00 - 227,400.00 USD annually