Post-Silicon ML Accelerator Validation Engineer I

Amazon Inc.; Austin (TX); Presencial; USD 116.000 - 142.000; Jornada completa

Descripción de la vacante

Annapurna Labs, an AWS organization, is seeking a Validation Engineer to own key validation across the full product lifecycle for ML accelerators powering AWS infrastructure. You will work with architecture, RTL, firmware, and software teams to ensure high-quality, scalable AI hardware validation across silicon, boards, and systems.

The role emphasizes cross-domain expertise—from low-level hardware interfaces to high-level ML workloads—while collaborating with multiple teams to deliver robust

Formación

• Bachelor’s or Master’s Degree in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or related fields.
• Strong programming skills in two or more: C/C++, Rust, Go, Python, Lua.

Responsabilidades

• Develop validation strategies and test plans from silicon bring-up to product release.
• Execute test plans from RTL simulation and emulation to physical silicon validation.
• Perform hands-on silicon bring-up and debugging using oscilloscopes, logic analyzers, and protocol analyzers.
• Validate ML accelerator performance, accuracy, and reliability on real neural network workloads.
• Build test infrastructure, CI/CD, and automated regression frameworks for scale.
• Collaborate across architecture, design, firmware, and software teams to triage failures and drive root cause analysis.
• Support production systems in AWS data centers and address field issues as they arise.

Conocimientos

Python

C/C++

Rust

Go

Linux

Git

CI/CD

Educación

Bachelor’s or Master’s Degree in Computer Science/Engineering/Data Science/Electrical Engineering

Herramientas

SystemVerilog/UVM

VCS

Questa

Xcelium

Palladium

Zebu

Veloce

Descripción del empleo

Annapurna Labs, an AWS organization, is seeking a Validation Engineer to own key validation across the full product lifecycle for ML accelerators powering AWS infrastructure. You will work with architecture, RTL, firmware, and software teams to ensure high-quality, scalable AI hardware validation across silicon, boards, and systems.

The role emphasizes cross-domain expertise—from low-level hardware interfaces to high-level ML workloads—while collaborating with multiple teams to deliver robust