Machine Learning Scientist

Company: Apple US Corp
Location: Austin, Texas, United States
Type: Full-time
Posted: 18.JUL.2021

Summary

SummarySummaryPosted: Jul 30, 2021 Weekly Hours: 40 Role Number:At Apple, we work every day to create products that enrich people's lives. O...

Description

SummarySummaryPosted: Jul 30, 2021 Weekly Hours: 40 Role Number:At Apple, we work every day to create products that enrich people's 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 and Discovery Ads in the 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 accomplished and ambitious individual who can thrive in a fast paced agile environment and work at the bleeding edge of ML and privacy frameworks. Our group is developing next generation of Ad Tech technology with a strong focus on user privacy and in the process it is redefining the industry. For end-users, we aim to provide high privacy guarantees and for advertisers we want to enable new mechanisms to build effective campaigns. This position involves working on large volumes of data, identifying 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. The role involves using state of the art language models, collaborative filters and dense representations. 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.Key Qualifications5+ years relevant experience in Algorithms, Artificial Intelligence, Distributed Systems, Machine Learning, Data Science or Statistics.You should have experience in software development using a general purpose programming language (e.g., Python, Java, C/C++, C#, Objective-C, and/or Swift).Previous experience working in any of the following: Privacy preserving machine learning algorithms such as Differential Privacy, Developing Risk models for Ad Fraud and Spam Detection, Developing Anomaly Detection models, Building deep representations based on language modeling & collaborative filtering, Developing audience segmentation models, attribution or lift models, Developing ML approaches, features for supporting search relevance & advertising performanceAbility to take requirements from design through to implementation both independently and with larger teamsClosely working with operational teams on deployment, monitoring, model retrain and other aspects of MLOpsExperience in distributed machine learning architectures and/or federated learningAny previous experience working with a public cloud infrastructure such as GCP, Azure or AWS is an added advantageDescriptionYou 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 frameworks such as TensorFlow and PyTorch. Implement and adapt deep learning network architectures, such as CNN and RNN. You would participate in cutting edge research and development in artificial intelligence and machine learning applications.Education & Experience- MS or PhD in Computer Science, Electrical Engineering or other STEM fields- Hands on experience working in a matrix organization and providing technical leadership to a team of 3-5 junior engineers.- Demonstrated experience in architecting and developing solutions to ambiguous problems with significant technical impact.- Interest and ability to invest in continual learning of new technical and soft skillsAdditional Requirements

 
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