Core OS machine learning and differential privacy team is looking for an exceptional engineer with strong background in machine learning and differential privacy to develop sophisticated algorithms, that will take advantage of Apple's ecosystem across platforms and devices to improve the user experience while respecting users privacy. In this unique and highly visible role, you will be at the center of Core OS machine learning and privacy technologies efforts. You are expected to generate and implement novel ideas that combine on-device learning with server side learning under data privacy constraints. Furthermore, you are expected to contribute towards the ever growing machine learning efforts at Apple, such as unsupervised feature learning, deep learning, scalability and speed-up of learning algorithms, to name a few. You will be a part of the group that is responsible for shipping components, which leverage machine intelligence to improve the user experience.
The position requires a highly motivated individual with a knack of thinking outside the box. This is the job unlike any other you’ve had. You’ll be challenged. You’ll be inspired. And you’ll be proud.
At least 2 years practical experience in using and developing privacy preserving machine learning or statistical algorithms
Proven track record of delivering concrete implementations
Excellent understanding of mathematical underpinnings of machine learning and data privacy
Good C/C++ skills
Knowledge of Python / R / Matlab / Mathematica is highly desirable
Highly professional, with the ability to deliver solid work on tight schedules
Develop and implement new machine learning algorithms on multiple platforms with strong focus on data privacy such as differential privacy
Exploit on-device and across-device data to improve the user experience
Work with cross-functional teams to prototype and explore new ideas to differentiate future iOS/ OS X products
Explore and communicate novel architectural solutions to senior management
M.S/Ph.D. in Machine Learning, Data Privacy, Artificial Intelligence, Statistics or a related discipline
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