Applied Science Manager

Job ID: 1326830 | Services LLC


We are growing our collaborative group of engineers and applied scientists by expanding into new areas. Come and join us as we invent new ways to delight Amazon customers.

Our goal is to understand what customers are looking for in whatever language happens to be their choice at the moment and help them find what they need in Amazon's vast catalog of billions of products.

As Launch Day Search Quality you will be the single threaded owner who will hire and grow a new team to drive improvements and mechanisms for Global Search Quality in (to-be-launched) international locales. You will invent mechanisms to evaluate and launch improvements for locales with a vast variety of languages, traffic patterns, cultures and preferences. You and your team will invent novel techniques that improve state of the art systems for low resource settings. You will invent and deploy techniques that work across languages, locales and different shopping modes.

Do no hesitate to reach out if you have some of the following: ability to apply state of the art in large scale Machine Learning (e.g. semi-weakly-un-supervised deep learning, natural language understanding, self-supervised learning), curiosity to learn through controlled experimentation and/or experience with low latency production systems.

You and your team will be able to deliver measure your impact for customers of the most popular shopping destination on this planet.

We are an inclusive employer and value diversity at Amazon. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.



· Master's degree in Computer Science or equivalent
· 8+ years experience applying Data Science
· Solid background in deep and/or statistical learning techniques for NLP (Transformers, CNNs, GANNs, HMMs, CRFs, SVMs, LDA, etc.)
· Solid programming skills in at least one programming language (Java, Python, etc.)
· Strong verbal and written communication skills
· Demonstrated technical leadership
· Experience mentoring and growing others


· Quantitative PhD a plus
· Experience working with real-world noisy data
· Strong problem solving skills
· Knowledge of foreign language(s)