Software Development Engineer, Amazon

• 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
• 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
• 3+ years of non-internship professional software development experience
• 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience programming with at least one software programming language

Desirable

• 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
• This is a great team to come to have a huge impact on AWS and the world's customers we serve!
• As a Software Development Engineer in the SageMaker HyperPod 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
• 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

• This position will remain posted until filled