Senior Pre-Silicon SoC Modeling Engineer, Annapurna Labs Machine Learning Accelerators, AWS

Amazon.com Inc

Cupertino, CA

JOB DETAILS
SKILLS
ASIC (Application Specific Integrated Circuit), Amazon Web Services (AWS), Architectural Analysis, Architectural Design, Architectural Services, C++ Programming Language, CPU (Central Processing Unit), Debugging Skills, Design Evaluation, Design Verification, GPU (Graphics Processing Unit), IP (Internet Protocol), Machine Learning, Model Validation, Performance Modeling, Product Lifecycle, RTL Design, RTL Verification, Regression Testing, Requirements Management, Software Engineering, System Architecture, System-on-a-Chip (SoC), Team Player, Testing, Verification Engineering
LOCATION
Cupertino, CA
POSTED
30+ days ago

AWSs Trainium and Inferentia chips power the worlds largest machine learning clusters. Our team builds C++ models of these custom SoCs that RTL designers, verification engineers, and software teams depend on throughout the silicon development lifecycle. Were looking for a modeling engineer to build and own models that directly impact how our chips are designed, verified, and brought to production.

What youll do:

  • Build and own models of SoC subsystems - translating architecture specs and RTL behavior into accurate, testable C++ models
  • Work directly with RTL design and verification teams to validate model behavior against RTL, debug discrepancies, and support pre-silicon verification flows
  • Develop model-based test infrastructure: regression suites, RTL correlation checks, and coverage-driven testing
  • Contribute to performance modeling efforts - building cycle-approximate models that help architects evaluate design trade-offs before RTL exists
  • Improve modeling methodology and infrastructure: how models are structured, integrated, tested, and released to DV and architecture teams
  • Collaborate with chip architects to understand upcoming designs and plan modeling work ahead of RTL availability

Why this role is interesting:

  • Your models are used to verify silicon before its built - bugs you catch save months of schedule and millions of dollars
  • Youll work at the intersection of software engineering and chip design, with deep visibility into how custom ML accelerators are architected
  • As the team scales, theres a clear path into architectural modeling - using your models to influence chip design decisions, not just validate them
  • Small team, high ownership, direct impact on AWSs most strategic silicon programs

You will thrive in this role if you:

  • Have built functional or performance models of SoCs, ASICs, GPUs, CPUs, or IP blocks
  • Are comfortable working with architectural / design specifications or reference implementations and translating them into C++ or SystemC models
  • Understand verification concepts and have worked with DV teams or in pre-silicon validation environments
  • Care about model fidelity and have experience correlating models against RTL or silicon
  • Are interested in expanding into architectural performance modeling as the team grows
  • Enjoy working on a small, high-impact team where you own significant pieces of the stack

No ML background needed. Youll learn the ML accelerator domain on the job.

This role can be based in Cupertino, CA or Austin, TX.

About the Company

A

Amazon.com Inc

At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles
COMPANY SIZE
10,000 employees or more
INDUSTRY
Retail
FOUNDED
1994
WEBSITE
http://Amazon.com/militaryroles