Technical Lead, Ad Platforms at Apple (Austin, TX)
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Location: Austin, TX
Type: Full Time
Created: 2021-04-12 05:00:24
At Apple, we work every day to create products that enrich peoples lives. Our Advertising Platforms group makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work. Today, our technology and services power advertising in Search Ads in App Store and Apple News. Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy. We are looking for an ambitious individual who can thrive in an agile environment. You will develop distributed systems and apply cutting edge algorithms and ML models to improve relevance across a range of advertising applications. The position involves large scale data infrastructure building as well as the capability to do big data analysis; detecting meaningful data patterns, assuring the integrity and breadth of the data, measuring user, campaign and app performance, and finally analyzing the results of extremely large-scale experiments. In addition, the successful candidate will also apply advanced ML techniques for federated learning where privacy mechanisms are safeguarded at the very onset and delightful relevance experiences are built by applying encryption techniques, on-device segmentation, advanced language models, ranking algorithms by utilizing the best of aggregated server and on-device data.You will have the opportunity to work on a platform with extreme scale and performance requirements. You would be applying your skills to work across the stack to develop, test, deploy and maintain ML based software solutions. Develop machine learning models using relevant technologies such as Tensor Flow, Py Torch, machine learning and image processing libraries. Implement and adapt deep learning architectures, such as GANs. You would participate in cutting edge research in artificial intelligence and machine learning applications.