Description de l'offre
Amazon’s Advertising technology team builds the technology infrastructure and ad serving systems to manage billions of advertising queries every day. The result is better quality advertising for publishers and more relevant ads for customers. Our infrastructure supports millions of Internet users and handles billions of queries per day, all delivered in milliseconds. Our data platform processes massive data sets to develop business intelligence and analytics that are critical for the efficiency and profitability of our advertising business.
Headline Search Advertising (HSA) is a self-service advertising program that drives discovery and sales on Amazon. This role is an opportunity to be part of the founding of a global product with the potential for explosive growth, standing at the intersection of e-commerce and advertising. Everyone on the team needs to be entrepreneurial, wear many hats, and work in a highly collaborative environment that’s more start-up than big company.
As a Software Development Engineer, you will:
· Develop highly scalable service to process millions of request per day and solve complex software systems problems by leverage state-of-the-art technology
· Apply machine learning techniques to improve predictive models and infrastructure
· Have unique exposure to technologies used in Search / Advertising / E-commerce platforms
· Work closely with our data-science and product managers to design experiments and implement end-to-end solutions
· Be a member of the Amazon-wide Software Development Community, participating in internal and external MeetUps, Hackathons and Conferences
Bachelor's degree in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, Statistics, Applied Mathematics, or related discipline
· At least 5 years’ experience in software design and development
· At lease 5 years’ experience programming in Java, Python, Scala, C++, or other popular language
· At least 4 years’ experience with either Internet-scale distributed technologies such as real-time recommendation, personalization, or search
· At least 1 year experience in training machine learning models or developing machine learning infrastructure