About The Position

In this job, you’ll develop the next frontier of mobile technology, in partnership with teams in sensing, Siri, and apps. Hungry for the responsibility to work on complex problems from end to end? You will conceptualize, explore, and define new inferential and predictive location- and motion-based capabilities for Apple's platforms. You will collect, curate, and analyze real-world data sets of varying size and complexity. You will aggregate, filter, and cluster data on mobile devices, from a variety of local sensors: GPS, WiFi, accelerometer, and others. You will design and implement algorithms, then integrate them into production code. You will test your work, dog-food it, collect metrics, and iterate. A dedication to users’ privacy and security is core to how Apple does business. We want their devices to exhibit the high level of intelligence and proactivity that can only come from deep contextual understanding. We don’t want their sensitive data coming back to Apple or being exposed to third parties.

Requirements

  • 5+ years experience developing commercial software.
  • Proficiency in Objective-C, C, modern C++, or Swift.
  • A working knowledge of statistics fundamentals.
  • Comfortable using histograms, basic probability, and Bayes’s Theorem.
  • Ability to evaluate and optimize for system performance: memory, CPU, radios, etc.

Nice To Haves

  • Real passion for the location domain.
  • Experience in location estimation—GPS/GNSS, WiFi positioning, indoor localization, or discrete localization.
  • A proven track record working effectively across teams.
  • Experience with Spark, Hadoop, or NoSQL data stores.

Responsibilities

  • Conceptualize, explore, and define new inferential and predictive location- and motion-based capabilities for Apple's platforms.
  • Collect, curate, and analyze real-world data sets of varying size and complexity.
  • Aggregate, filter, and cluster data on mobile devices from a variety of local sensors: GPS, WiFi, accelerometer, and others.
  • Design and implement algorithms, then integrate them into production code.
  • Test your work, dog-food it, collect metrics, and iterate.
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