Software Development Engineer II, SageMaker HyperPod Data Plane

About the role

At AWS AI, we want to make it easy for our customers to train their deep learning workload in the cloud. With Amazon SageMaker, AWS is building customer-facing services to empower data scientists and software engineers in their deep learning endeavors. As our customers rapidly adopt LLMs and Generative AI for their business, we’re building the next-generation AI platform to accelerate their development. We’re seeking a dedicated engineering team lead to drive building our next-generation AI compute platform that’s optimized for LLMs and distributed training.

As an SDE, you will be responsible for designing, developing, testing, and deploying distributed machine learning systems and large-scale solutions for our world-wide customer base. In this, you will collaborate closely with a team of ML scientists and customers to influence our overall strategy and define the team’s roadmap. You'll assist in gathering and analyzing business and functional requirements, and translate requirements into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture. You will also drive the system architecture, spearhead best practices that enable a quality product, and help coach and develop junior engineers. A successful candidate will have an established background in engineering large scale software systems, a strong technical ability, great communication skills, and a motivation to achieve results in a fast paced environment.

About You:

You are passionate about building platform and products for large scale deep learning model training (100+ billion parameter GPT, 1000s of GPU devices). You have a proven track record of bringing innovative research to customers. You are able to thrive and succeed in an entrepreneurial environment and not be hindered by ambiguity or competing priorities. Ownership, delivering results, thinking big and analytical leadership are essential to success in this role.

You have solid experience in multi-threaded asynchronous C++/Go development. You have prior experience in resource orchestrators with kubernetes, high performance computing, building scalable systems, experience in large language model training.

This is a great team to come to have a huge impact on AWS and the world's customers we serve!

Key job responsibilities

As a Software Development Engineer in the SageMaker team, you will be responsible for:

- Developing innovative solutions for supporting Large Language Model training in a cluster of nodes;

- Develop and maintain a performant, resilient and fully-managed service built to train large-scale foundation models.

- Optimizing distributed training by profiling, identifying bottlenecks and addressing them by improving compute and network performance, as well as finding opportunities for better compute/communication overlap;

- You will serve as a key technical resource in the full development cycle, from conception to delivery and maintenance.