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

AWS's Trainium and Inferentia chips power the world's 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. We're looking for a modeling engineer to build and own models that directly impact how our chips are designed, verified, and brought to production.

What you'll 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 it's built — bugs you catch save months of schedule and millions of dollars
• You'll work at the intersection of software engineering and chip design, with deep visibility into how custom ML accelerators are architected
• As the team scales, there's 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 AWS's 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. You'll learn the ML accelerator domain on the job.
• This role can be based in Cupertino, CA or Austin, TX.