Sr. Software Engineer- Ai/Ml, Aws Neuron Distributed Training

Sr.Software Engineer- AI/ML, AWS Neuron Distributed Training Annapurna Labs designs silicon and software that accelerates innovation.Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday.Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.AWS Neuron is the complete software stack for the AWS Trainium (Trn1/Trn2) and Inferentia (Inf1/Inf2) our cloud-scale Machine Learning accelerators.This role is for a Senior Machine Learning Engineer in the Distributed Training team for AWS Neuron, responsible for development, enablement and performance tuning of a wide variety of ML model families, including massive-scale Large Language Models (LLM) such as GPT and Llama, as well as Stable Diffusion, Vision Transformers (ViT) and many more.The ML Distributed Training team works side by side with chip architects, compiler engineers and runtime engineers to create, build and tune distributed training solutions with Trainium instances.Experience with training these large models using Python is a must.FSDP (Fully-Sharded Data Parallel), Deepspeed, Nemo and other distributed training libraries are central to this and extending all of this for the Neuron based system is key.Key job responsibilitiesBuild distributed training support into PyTorch and JAX using XLA, the Neuron compiler, and runtime stacks.Optimize models to achieve peak performance and maximize efficiency on AWS custom silicon, including Trainium and Inferentia, as well as Trn2, Trn1, Inf1, and Inf2 servers.Apply strong software development skills, deep-dive abilities, cross-functional team collaboration, and a solid foundation in Machine Learning.About the teamAnnapurna Labs was a startup company acquired by AWS in ****, 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 Nitro, ENA, EFA, Graviton and F1 EC2 Instances, AWS Neuron, Inferentia and Trainium ML Accelerators, and in storage with scalable NVMe, are some of the products we have delivered, over the last few years.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.Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews.We care about your career growth and strive to assign projects that help your engineering expertise so you feel empowered to take on more complex tasks in the future.Basic QualificationsBachelor's degree in computer science or equivalent5+ years of non-internship professional software development experience5+ years of programming with at least one software programming language experience5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experienceExperience as a mentor, tech lead or leading an engineering teamExperience in machine learning, data mining, information retrieval, statistics or natural language processingPreferred QualificationsMaster's degree in computer science or equivalentExperience in computer architecturePrevious software engineering expertise with Pytorch/Jax/Tensorflow, Distributed libraries and Frameworks, End-to-end Model Training.Compensation and BenefitsOur compensation reflects the cost of labor across several US geographic markets.The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/year in our highest geographic market.Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience.Amazon is a total compensation company.Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.For more information, please visit .This position will remain posted until filled.Applicants should apply via our internal or external career site.Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.#J-*****-Ljbffr