DESCRIPTION

Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.

Our systems and algorithms operate on one of the world's largest product catalogs, matching shoppers with advertised products with a high relevance bar and strict latency constraints. We work hand-in-hand with Machine Learning and NLP research scientists to come up with novel solutions that deliver highly relevant ads. We consistently strive to improve the customer search and detail page experiences. You will drive appropriate technology choices for the business, lead the way for continuous innovation, and shape the future of e-commerce. This is an opportunity to make a significant impact on the future of the Amazon vision.

Key job responsibilities
As a Software Development Engineer in Machine Learning at Amazon, you will drive the technical direction of our offerings and solutions, working with many different technologies across the sponsored products organization. You will design, code, troubleshoot, and support scalable machine-learning pipelines and online serving systems. You will work closely with applied scientists to optimize the performance of machine-learning models and infrastructure, and implement end-to-end solutions. What you create is also what you own.

About the team
We are pioneers in applying advanced machine learning and generative AI algorithms in Sponsored Products business. We develop customized CTR and CVR prediction models to help shopper feel understood and shop efficiently on off search placements (including product detail pages, thank you pages, home pages, etc.). We develop generative models to understand shopper intent and preference and predict next action.