Sr. Software Development Engineer- AI / ML, AWS Neuron Apps
Job ID : 2783229 Amazon.com Services LLC - A57
Below, you will find a complete breakdown of everything required of potential candidates, as well as how to apply Good luck.
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 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
- 5+ years of programming using a modern programming language such as Java, C++, or C#, including object-oriented design experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Fundamentals of Machine learning and deep learning models, their architecture, training and inference lifecycles along with work experience on some optimizations for improving the model execution.
PREFERRED QUALIFICATIONS
Master's degree in computer science or equivalent
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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