Device Driver Engineering Manager, Annapurna Labs Machine Learning Acceleration, AWS

Description

Custom silicon chips live at the heart of AWS Machine Learning servers, and this team builds the backend software that runs these servers. We’re looking for someone to lead our SoC (System on Chip) device-driver / HAL (Hardware Abstraction Layer) software team. You'll help us deliver at scale as we build the next generation of SoC software. This is a hands‑on, in‑the‑trenches leadership position, where you’ll manage systems, debug issues, and write code alongside your team.

As the Manager for SoC driver software, you will:

• Manage a team of 6 developers

• Work with hardware designers to write drivers for newly developed SoC IPs

• Work with system software teams to solve SoC and system‑level architectural issues, drive debug, and innovate on cross‑functional solutions

• Refactor and maintain existing codebases throughout the device lifecycle

• Continuously test and deploy your software stack to multiple internal customers

• Innovate on the tooling you provide to customers, making it easier for them to use and debug our So Cs

Annapurna Labs, our organization within AWS, designs and deploys some of the largest custom silicon in the world, with many subsystems that all must be managed, tested, and monitored. The SoC drivers are a critical piece of the AWS infrastructure management software stack that ensures the chip is functional, performant, and secure.

You will thrive in this role if you:

• Enjoy building, managing, and leading small teams

• Love solving complex system‑level issues

• Are proficient in C++ and familiar with Python

• Know how to build effective abstractions over low‑level SoC details

• Are familiar with modular driver architectures (such as the Linux or Windows driver stacks)

• Have strong opinions about software architecture, and are able to apply them effectively

• Enjoy learning new technologies, building software at scale, moving fast, and working closely with colleagues as part of a small, startup‑like team within a large organization

Although we build and deploy machine learning chips, no machine learning background is needed for this role. Your team (and your software) won’t be doing machine learning. Our driver stack lives at the lowest level of the backend AWS infrastructure responsible for managing our ML servers. You and your team will develop drivers for components used by machine learning, like PCIe and HBM, but won’t need to deeply understand ML yourselves.

This role can be based in either Cupertino, CA or Austin, TX. The team is split between the two sites, with most of the team sitting in Cupertino, and customers in both.

We're changing an industry. We're searching for individuals who are ready for this challenge, who want to reach beyond what is possible today. Come join us and build the future of machine learning!

For a taste of our team's products and culture, check out our most recent success story with Trainium3:

• 3+ years of engineering team management experience

• 7+ years of non‑internship professional software development experience

• 7+ years of programming using a modern programming language such as Java, C++, or C#, including object‑oriented design experience

• 4+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience

• Experience leading the design, build and deployment of complex and performant (reliable and scalable) software solutions in production

• 2+ years of C++ development experience

• Experience developing software for hardware (SoC, ASIC, GPU, CPU, etc.)

• Experience communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs

• Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers

• Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence

Amazon is an equal opportunity…