EFA Network Sr. Software Engineer, EFA ML Software Team

Amazon • Seattle, WA

63d

About The Position

Want to help make the next generation of Machine Learning in the cloud possible? Do you have a laser focus on performance in your team's code? We want to talk to you! We own the user-space software that makes the Elastic Fabric Adapter (EFA) network card work for Machine Learning (ML) and High-Performance Computing (HPC) customers on AWS. Across multiple projects written in C, our team enables customers to network thousands of GPU and CPU instance types to handle the toughest clustered workloads. Lead a dynamic, fast-paced group that has a big impact every day on the hottest companies doing AI and HPC today.

Requirements

• 5+ years of non-internship professional software development experience
• 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
• Min 5+ years programming in C at a low level.

Nice To Haves

• Bachelor's degree in computer science or equivalent

Responsibilities

• Help lead a team of obsessed networking developers operating at the highest levels in networking.
• Write the highest-performing code in C for multiple open source projects supporting EFA, such as Libfabric and Open MPI.
• Work with multiple teams in the stack to invent new APIs for the latest concepts in networking in the cloud.
• Dive deep into how your customers are doing collectives and messaging at high bandwidth and low latency.
• Provide expert-level support to some of the biggest names in AI in the world.
• Start from the needs of your customer and invent new ways of cutting the occupancy of the software stack for EFA.
• Drive your peers and leadership to accept your excellent written designs.
• Work with our ML Infrastructure team to see your products perform on 100s and 1000s of top-end machine clusters.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level