Applied Scientist, Advertising Trust

Saved job 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.

The Advertising Trust org is responsible for ensuring that ads are relevant and is of good quality, leading to higher conversion for the sellers and providing a great experience for the customers. We deal with one of the world’s largest product catalog, handle billions of requests a day with plans to grow it by order of magnitude and use automated systems to validate tens of millions of offers submitted by thousands of merchants in multiple countries and languages.

Key job responsibilities

In this role, you will build and develop AI Agents and ML models to address content understanding problems in Ads and communicating moderation outcomes and advertising policies to advertisers. These agents and models will rely on a variety of multimodal, visual and textual features requiring expertise in these domains. These models need to scale to multiple modalities, languages and countries. You will collaborate with engineers and other scientists to build, train and deploy these agents and models. As part of these activities, you will develop production level code that enables moderation of millions of ads submitted each day. You will also help definite and measure relevant metrics for the business.

Requirements: - 3+ years of building models for business application experience

- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience

- Experience in patents or publications at top-tier peer-reviewed conferences or journals

- Experience programming in Java, C++, Python or related language

- Experience building machine learning models or developing algorithms for business application

- Experience in solving business problems through machine learning, data mining and statistical algorithms

- Experience with neural deep learning methods and machine learning

- Experience with neural deep learning methods and machine learning