Software Development Engineer, SageMaker HyperPod Data Plane

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.
• You will own delivery of entire piece of the system and serve as technical lead on complex projects using best practice engineering standards
• Hire/mentor junior development engineers

A day in the life

Every day will bring new and exciting challenges on the job while you:

• Build and improve next-generation AI platform using Kubernetes as orchestration layer.
• Collaborate with internal engineering teams, leading technology companies around the world and open source community - PyTorch, NVIDIA/GPU
• Create innovative products to run at scale on the AI platform, and see them launched in high volume production

About the team

Inclusive Team Culture

Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences. Amazon's culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Work/Life Balance

Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Mentorship & Career Growth

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.