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 like GPT2, GPT3 and beyond, as well as stable diffusion, Vision Transformers, and many more.
The ML Apps team works side by side 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 a must. FSDP, Deepspeed, and other distributed training libraries are central to this, and extending all of this for the Neuron-based system is key.
Key job responsibilities
This role will help lead the efforts building distributed training and inference support into Pytorch, Tensorflow, Jax using XLA and the Neuron compiler and runtime stacks. This role will help tune these models to ensure highest performance and maximize the efficiency of them running on the customer AWS Trainium and Inferentia silicon and the TRn1, Inf1 servers. Strong software development and ML knowledge are both critical to this role.
BASIC QUALIFICATIONS
- 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
PREFERRED QUALIFICATIONS
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
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