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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 ATT team, based in Bangalore, is responsible for ensuring that ads are relevant and are 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 an order of magnitude and use automated systems to validate tens of millions of offers submitted by thousands of merchants in multiple countries and languages.

We are searching for pioneers who are passionate about innovating and building state-of-the-art technologies for content understanding, labelling and generation in ads. In this role as an Applied Science Manager, you will drive a science charter and lead a team of applied scientists to develop novel scientific solutions to solve real-world problems for ads moderation and labelling, collaborate with cross functional leaders to define science strategies and lead your team to deliver product driven science solutions. This includes developing computer vision and machine learning models/methods (including but not limited to deep learning models, generative AI based models/solutions, large language models (LLMs) and vision language models (VLMs). - 3+ years of scientists or machine learning engineers management experience
- Knowledge of ML, NLP, Information Retrieval and Analytics
- PhD, or Masters degree and 5+ years of building machine learning models or developing algorithms for business application experience