SoC Systems Software Engineer — ML Accelerators

Amazon Web Services (AWS); Austin (TX); On-site; USD 144,000 - 194,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Annapurna Labs (U.S.) Inc. in Austin, TX, is seeking a Systems Software Engineer to work at the boundary between hardware and software, tackling hard pre-silicon and post-silicon problems that power large ML workloads.

You will design and maintain SoC models, debug hardware/software interactions, and collaborate with chip architects, RTL designers, modelers, and ML teams to validate interfaces. This role offers hands-on ownership of critical stack components and opportunities to influence the

Qualifications

• Knowledge of hardware architectures.
• 2+ years of professional experience developing firmware, drivers, runtime software, or low-level systems software for custom hardware (SoCs, ASICs, GPUs, CPUs, FPGAs).
• Experience programming in C++, Python, and/or Rust (preference for at least 2).

Responsibilities

• Develop and own components of SoC models, single-chip and datacenter-scale.
• Debug hardware/software interactions across the full stack—from register-level bring-up on models to performance analysis on silicon.
• Collaborate with chip architects, RTL designers, modelers, compiler engineers, and ML framework teams to co-design interfaces.
• Contribute to hardware feature design from a software perspective in early chip development.
• Build tooling, test infrastructure, and automation to accelerate development.

Skills

Hardware architectures

C++

Python

Rust

Tools

QEMU

FPGA

Emulators

Job description

Annapurna Labs (U.S.) Inc. in Austin, TX, is seeking a Systems Software Engineer to work at the boundary between hardware and software, tackling hard pre-silicon and post-silicon problems that power large ML workloads.

You will design and maintain SoC models, debug hardware/software interactions, and collaborate with chip architects, RTL designers, modelers, and ML teams to validate interfaces. This role offers hands-on ownership of critical stack components and opportunities to influence the