Software Engineer- AI/ML, AWS Neuron Distributed Training Do you love decomposing problems to develop products that impact millions of people around the world? Would you enjoy identifying, defining, and building software solutions that revolutionize how businesses operate? The Annapurna Labs team at Amazon Web Services (AWS) is looking for a Software Development Engineer II to build, deliver, and maintain complex products that delight our customers and raise our performance bar. You’ll design fault-tolerant systems that run at massive scale as we continue to innovate best-in-class services and applications in the AWS Cloud. Annapurna Labs was a startup company acquired by AWS in 2015, and is now fully integrated. If AWS is an infrastructure company, then think Annapurna Labs as the infrastructure provider of AWS. Our org covers multiple disciplines including silicon engineering, hardware design and verification, software, and operations. AWS Neuron, Inferentia and Trainium ML Accelerators, and related storage technologies are among the products we have delivered. AWS Neuron is the complete software stack for the AWS Inferentia and Trainium cloud-scale machine learning accelerators and the Trn1 and Inf1 servers that use them. This role is for a senior software engineer in the Machine Learning Applications (ML Apps) team for AWS Neuron. This role is responsible for development, enablement and performance tuning of a wide variety of ML model families, including massive scale large language models, diffusion models, Vision Transformers and more. The ML Distributed Training team works with chip architects, compiler engineers and runtime engineers to create, build and tune distributed training solutions with Trn1. Experience training these large models using Python is required. FSDP, Deepspeed and other distributed training libraries are central to this effort and will be extended for the Neuron-based system. Key job responsibilities Help lead the efforts building distributed training support into PyTorch, TensorFlow using XLA and the Neuron compiler and runtime stacks. Tune models to ensure high performance and maximize efficiency on AWS Trainium and Inferentia silicon and the Trn1/Inf1 servers. Possess strong software development and ML knowledge to drive software solutions at scale. About the team Inclusive team culture with emphasis on belonging and learning. Work/life balance and flexible working hours to support personal and professional well-being. Mentorship and career growth with projects aligned to develop members' skills for more complex tasks. Basic Qualifications 3 years of non-internship professional software development experience 3 years of non-internship design or architecture experience (design patterns, reliability and scaling) of new and existing systems Experience programming with at least one software programming language Deep Learning industry experience Preferred Qualifications 3 years of full software development life cycle experience (coding standards, code reviews, source control, build processes, testing, operations) Bachelor's degree in computer science or equivalent Experience with PyTorch/Jax/TensorFlow, distributed libraries and frameworks, end-to-end model training; experience optimizing large DL models on Trainium architecture Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation during the application and hiring process, please visit the AWS accommodations page for more information. Applicants should apply via our internal or external career site. This position will remain posted until filled. Compensation information is available on the job posting and may include base pay, equity, and other benefits. For more information, please visit Amazon’s benefits page. J-18808-Ljbffr