1 week ago
Senior Applied Scientist , Search Science and AI - Search M5
US, WA, Seattle
Amazon is the 4th most popular site in the 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 search 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 very large 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 apply them to a problem of this magnitude. Some exciting questions that we expect to answer over the next few years include:
- Can combining supervised multi-task training with unsupervised training help us to improve model accuracy?
- Can we transfer our knowledge of the customer to every language and every locale ?
- Can a focus on compilers and custom hardware help us accelerate model training and reduce hardware costs?
This is a unique opportunity to get in on the ground floor, shape, and build the next-generation of Amazon Search. We are looking for exceptional scientists and ML engineers who are passionate about innovation and impact, and want to work in a team with a startup culture within a larger organization.
Key job responsibilities
Train large deep learning models with hundreds of billions parameters. Set science directions for the team, in areas such as efficient model architecture, training and data optimization/scaling, model/data/pipeline parallel techniques, and much more.
- Can combining supervised multi-task training with unsupervised training help us to improve model accuracy?
- Can we transfer our knowledge of the customer to every language and every locale ?
- Can a focus on compilers and custom hardware help us accelerate model training and reduce hardware costs?
This is a unique opportunity to get in on the ground floor, shape, and build the next-generation of Amazon Search. We are looking for exceptional scientists and ML engineers who are passionate about innovation and impact, and want to work in a team with a startup culture within a larger organization.
Key job responsibilities
Train large deep learning models with hundreds of billions parameters. Set science directions for the team, in areas such as efficient model architecture, training and data optimization/scaling, model/data/pipeline parallel techniques, and much more.