DESCRIPTION

We're looking for an experienced Applied Scientist with exceptional technical, analytical, and innovative capabilities to research, design, and create elegant machine learning solutions. Your solutions will help our advertisers with multi-media and multi-lingual advertising offerings, leveraging Generative AI, Deep Neural Networks, Natural Language Processing (NLP), and Computer Vision (CV). You will build ML models that localize multi-media advertising contents, including text, images and videos. You will also identify opportunities to leverage ML beyond localization, including, international expansion and global advertising. Your work will directly impact our customers in the form of products and services used directly by our advertisers as well as our third-party integrators.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our businesses driving long term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

The Advertiser Growth Engine (AGE) team owns and builds services and applications across Amazon World-Wide Advertising that make advertising across countries/languages as easy as flipping a switch. We are focused on: (1) expanding Amazon Ads advertiser base, and (2) eliminating localization, operational, and marketplace knowledge gap barriers for Advertisers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth globally.

Key job responsibilities
As an Applied Scientist on this team, you will:
- Build and deliver end-to-end machine learning solutions; build ML models and perform data analysis to deliver scalable solutions to business problems.
- Work closely with senior leaders across science, engineering, and product disciplines to drive the team's roadmap and establish business requirements.
- Perform hands-on analysis and modeling with enormous data sets to develop insights that increase traffic monetization and merchandise sales without compromising shopper experience.
- Run A/B experiments that affect hundreds of millions of customers, evaluate the impact of your optimizations and communicate your results to various business stakeholders.
- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
- Research new innovate machine learning approaches.