Senior Embedded Software Engineer - ML Hardware & Firmware

Amazon Inc.; Austin, Northern (TX, KY); Hybrid; USD 168,000 - 227,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Job summary

Annapurna Labs, part of Amazon, seeks a Sr Embedded Software Engineer to lead architecture for ML software and firmware across high-performance hardware platforms. You will work with EC2 teams and manufacturing partners, mentoring engineers while driving qualification processes and delivering robust device drivers and ML infrastructure.

You will write efficient C/C++ code, develop drivers, and shape the software stack for NeuronSwitches and Trainium-scale systems, in a hands-on hardware-software

Qualifications

• 5+ years of non-internship professional software development experience.
• 5+ years of programming with at least one software language (C/C++).
• 5+ years of leading design or architecture of new and existing systems.
• 5+ years of full software development life cycle, including coding standards, reviews, source control, builds, testing, and operations.
• Experience mentoring, tech lead, or leading an engineering team.

Responsibilities

• Define technical strategy and lead architecture for Annapurna Labs' ML platform.
• Collaborate with EC2 teams and manufacturing partners for seamless system integration.
• Own end-to-end qualification frameworks and mentor engineers on best practices.
• Drive end-to-end qualification processes for new software implementations.
• Craft high-performance software solutions running on Linux.

Skills

C/C++

Linux

Architecture

Mentor / Tech lead

Education

Bachelor's degree in Computer Science or equivalent

Job description

Annapurna Labs, part of Amazon, seeks a Sr Embedded Software Engineer to lead architecture for ML software and firmware across high-performance hardware platforms. You will work with EC2 teams and manufacturing partners, mentoring engineers while driving qualification processes and delivering robust device drivers and ML infrastructure.

You will write efficient C/C++ code, develop drivers, and shape the software stack for NeuronSwitches and Trainium-scale systems, in a hands-on hardware-software