Amazon is the 4th most popular site in the US (http://www.alexa.com/topsites/countries/US). Our product search engine is one of the most heavily used services in the world, indexes billions of products, and serves hundreds of millions of customers world-wide. We are working on a new AI-first initiative to re-architect and reinvent the way we do LLM through the use of extremely large scale, next-generation deep learning techniques. Our goal is to make step function improvements in the use of advanced Machine Learning (ML) on an immense scale datasets; specifically through the use of aggressive systems engineering and hardware accelerators. This is a rare opportunity to develop cutting-edge ML solutions, and have the opportunity to apply them to a problem of this magnitude. Some exciting questions that we expect to answer over the next few years include:
- Can we transfer the knowledge we learned from Amazon data to all Amazon business applications?
- How to accelerate model training and inference at super large scale?
- How to build the world-class large scale ML training capability specially for deep learning models?
This is a unique opportunity to get in on the ground floor, shape and build the next-generation of Stores Foundational AI. We are looking for dedicated and forward-thinking machine learning engineers who are passionate about innovation, impact, and want to work on a team with an exciting startup culture!

Key job responsibilities
- Understand different business problems at Amazon such as Search, Ads, Recommendation, etc. Build machine learning models to push the boundary of Amazon business.
- Build the world class distributed training ML techniques.
- Identify deep learning model training and inference bottleneck and use innovative solution to solve them.