Lead Software Engineer, ML Network Stack - Annapurna Labs

Lead Software Engineer, ML Network Stack - Annapurna Labs

Job :  |  Services LLC

We are seeking an experienced engineer and technical leader to join our team that owns the network stack for EC2 distributed AI/ML systems. The team develops support for a variety of frameworks and communication libraries including NCCL, NVSHMEM, NIXL, NCCL GIN, and CUDA kernels. Solid knowledge of Linux, networking, and performant coding is important. Experience with embedded systems is valued, and experience with high-speed networking or HPC/RDMA interconnects is highly valued.

If you like solving hard problems, want to work with HPC and ML customers, iterate fast and deliver meaningful solutions at scale, then come join us! This truly is a role at the forefront of AI/ML—you'll be working on features for the largest clusters, with the largest customers, for the largest AI models.

The organization you would be joining is Annapurna Labs, an integral part of AWS that develops hardware and software components that are critical building blocks for EC2 infrastructure. Every instance in EC2 is running some type of hardware designed by Annapurna Labs. We specialize in designing software, systems, and chips that optimize the AWS customer experience.

Key job responsibilities
Be the Leader which works across the NVIDIA ML communication stack for enabling NVIDIA GPUs to work with the AWS EC2 machines. Knowledge of ML Networking, ML applications, and frameworks will be highly regarded. You'll be leading senior, mid-level, and junior SDEs and directing work to ensure the team delivers functions and features required for the latest and largest ML workloads.

Come be a part of an organization that has developed some of the foundational technologies in AWS and EC2. Annapurna Labs' inventions are routinely mentioned in keynotes and all of re:

Invent. Do you recognize Nitro, Trainium, EFA, ENA-X, Inferentia, Graviton? Join us and help create the future. We are seeking Senior SDE's interested in moving to an SDM role after ramp.

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.

Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences.

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Experience as a mentor, tech lead or leading an engineering team, or experience in development in the last 3 years
• 5+ years of experience with programming language: C or C++

• Bachelor's degree in computer science or equivalent
• Experience…