ML Network Stack Lead Engineer

Amazon; Cupertino, Northern (CA, KY); Híbrido; USD 193.000 - 262.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

401(k) matching

Paid time off

Parental leave

Descripción de la vacante

Annapurna Labs, an integral part of AWS, Cupertino, seeks a Lead Software Engineer to own the ML networking stack for EC2 distributed AI/ML systems. You will guide design across ML communication libraries (NCCL, NVSHMEM, NIXL) and CUDA kernels, mentoring engineers and shaping scalable software.

You will work on large-scale clusters, collaborate with hardware teams, and drive features for the largest AI models. Requires 5+ years leading design and C/C++ expertise.

Formación

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

Responsabilidades

• 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.

Conocimientos

Leadership

Architecture design

C/C++

Mentorship

SDE leadership

Educación

Bachelor's degree in computer science or equivalent

Herramientas

ML Communication Libraries

RDMA Networking

Descripción del empleo

Annapurna Labs, an integral part of AWS, Cupertino, seeks a Lead Software Engineer to own the ML networking stack for EC2 distributed AI/ML systems. You will guide design across ML communication libraries (NCCL, NVSHMEM, NIXL) and CUDA kernels, mentoring engineers and shaping scalable software.

You will work on large-scale clusters, collaborate with hardware teams, and drive features for the largest AI models. Requires 5+ years leading design and C/C++ expertise.