Data Science & Machine Learning Internship at Apple

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Applications Open: November 10, 2017

Apple - Building

Jobs at Apple are rewarding and enriching, both personally and professionally. They are available in a wide range of fields, including in stores, corporate workings, and at home. Apple also offers several internship opportunities to qualified students.

On November 9, 2017, Apple announced the Data Science and Machine Learning Internship through Apple Maps. This job is located in Santa Clara Valley, California and requires a full forty hours of work a week.

The intern will join the Apple Maps Routing and Traffic team in 2018. This team works on some of the most challenging and significant big data issues in the modern computer engineering field. The group works to make sense of petabytes of data in order to deliver critical navigational functionality for the millions of users who depend on the success of Apple Maps.

This internship is a great opportunity for a motivated, talented student looking to apply his or her coding and machine learning skills to a large, significant application. The ideal intern will have experience in machine learning theory and practice, in particular neural networks and sequence-based models. He or she will also have used machine learning software such as Python Sci-Kit, TensorFlow, Weka, MATLAB, or R. The successful candidate will have in-depth experience in Java or Python, along with CS fundamentals and object-oriented programming. Experience with Hadoop or Spark is an additional bonus.

This internship will allow the candidate to practice skills necessary to develop novel solutions to improve the quality of traffic information, routes, navigation, and ETA using large-scale streaming data. Interns will work closely with experts in machine learning and traffic and solve interesting data-driven projects. Interns should be currently enrolled in Ph.D. studies in Computer Science, Mathematics, Statistics, Civil Engineering (Traffic with a data science focus), or a related field.

To learn more and apply, click here.


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