Applied Scientist, AWS AI
At Amazon AI, the Deep Engine Science team is working on machine learning systems to accelerate deep learning workloads on multiple hardware platforms, with the goal of making it easy for our customers to get good execution performance for machine learning models everywhere.
The AWS Deep Engine Science team is growing rapidly to keep up with the latest progress of the machine learning systems field to better serve our customers. We are hiring well-rounded applied scientists and software developers with backgrounds in machine learning, foundation model, compilers, systems, distributed computing, and AI accelerators. If you have worked on HPC and performance tuning, you will enjoy working on the breadth of ML applications that we optimize.
As a machine learning systems developer/researcher, you will work on systematic approaches to improve the performance of deep learning models, with a focus on deep learning compilers such as Apache TVM, and large foundation model training and inference. The work offers an extremely broad set of opportunities to work in full stack with exposure to multiple AI applications, ML frameworks, models, compilers, systems SW, and various AI hardware including ARM, Intel, Nvidia, AWS Trainium/Inferentia, and emerging edge AI ASICs. Working at the frontier of the field, you will have the opportunity to publish in the top-tier systems and machine learning conferences.
Join the AWS Deep Engine Science team to develop machine learning systems to help AWS customers train and deploy machine learning models in the cloud and on edge devices at scale in production.