SoC Systems Software Engineer - ML Accelerator Stack

Amazon Web Services (AWS)

Cupertino (CA)

In loco

USD 165.000 - 224.000

Tempo pieno

14 giorni+
Generatore di candidature

Una candidatura su misura per questa offerta di lavoro — un curriculum e una lettera di presentazione personalizzati, perfettamente in linea con l'annuncio.

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Vantaggi offerti da questo lavoro

Health insurance
401(k)
Paid time off
Parental leave

Descrizione del lavoro

Annapurna Labs, AWS's silicon organization, seeks a Systems Software Engineer to work at the hardware–software boundary across pre-silicon and post-silicon challenges. You will help model, validate, and optimize SoCs and the surrounding software stack.

You will collaborate with chip architects, RTL designers, modelers, and ML framework teams to co-design interfaces, build tooling and run-time software, and drive performance on large-scale ML workloads.

Competenze

  • Knowledge of hardware architectures and how software interfaces with hardware.
  • Experience with firmware, drivers, or low-level systems software for custom hardware.
  • Proficiency in C++ and Python with ability to write tooling for hardware/software stacks.

Mansioni

  • Develop and own components of SoC models at single-chip and datacenter-scale levels.
  • Debug complex hardware/software interactions across the full stack, from models to live silicon.
  • Collaborate with chip architects, RTL designers, modelers, compiler engineers, and ML framework teams.

Conoscenze

Reading hardware specs
Debugging hardware/software interfaces
Firmware/Drivers
Performance profiling
C++ close to hardware
Python for tooling
System-level thinking
Small-team ownership

Strumenti

QEMU
FPGA
Emulators

Descrizione del lavoro

Annapurna Labs, AWS's silicon organization, seeks a Systems Software Engineer to work at the hardware–software boundary across pre-silicon and post-silicon challenges. You will help model, validate, and optimize SoCs and the surrounding software stack.

You will collaborate with chip architects, RTL designers, modelers, and ML framework teams to co-design interfaces, build tooling and run-time software, and drive performance on large-scale ML workloads.

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