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.

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The Facebook Artificial Intelligence (AI) Research Residency Program seeks applicants for its 2018-2019 program. This one-year residency is designed to give candidates hands-on experience in machine learning research. Successful residents are paired with senior researchers or engineers, who will serve as mentors. Throughout the duration of the program, researchers will work to research a problem of mutual interest and incorporate new techniques to solve that problem.

Collaboration will occur both with the mentor and with other departments. Research will be communicated by the submission of papers to top academic venues, such as NIPS, ICML, ICLR, CVPR, and others, as well as open-source code releases. This is a full-time program that cannot be undertaken with any other employment or studies.

Upon completion of this residency, participants will be prepared for graduate programs in machine learning or to begin a successful research career in the field. Applications are encouraged from individuals with strong technical backgrounds who are passionate about AI research. Applicants with prior experience in machine learning are given preference, but this is not a requirement. Those with backgrounds in math, physics, finance, economics, linguistics, computational social science, and bioinformatics are encouraged to apply.

The successful applicant will have a Bachelor’s degree in a STEM field and coursework in Linear Algebra, Probability, and Calculus. He or she will also have coding experience in languages such as Python or C/C++. They will also have familiarity with platforms such as PyTorch, Caffee, Theano, or TensorFlow.

Residents will be based in Facebook Menlo Park and New York. If work visas are required, they may be obtained. Residents will learn how to perform research in deep learning and AI, and will understand prior work and existing literature. They will work with research mentors and translate ideas into code. They will also write up research results in academic papers.

Applicants should complete the online application and submit a CV/resume that includes links to GitHub, professional webpages, publications, or blog posts. They should also provide personal statements and academic transcripts.

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The Google AI Residency Program (formerly known as the Google Brain Residency Program) is being offered starting in the summer of 2018. This year-long program is designed to advance participants’ careers in machine learning research. Residents will work with distinguished scientists from various teams in order to become established AI researchers.

This program was created in 2015 and has been recently expanded to include a broader group of research teams. This program allows residents to publish their work externally and develop a strong reputation in the field of research. Residents will conduct original, fundamental research and contribute to services utilized by millions of individuals.

This program is ideal for individuals who want to learn how to conduct machine learning research, especially in collaboration with other qualified researchers. Candidates with limited experience in machine learning or related fields may apply, as may those who have research experience in another field (such as mathematics, physics, bioinformatics, etc).

Qualified applicants will have a minimum of a Bachelor’s degree in a STEM field, such as Mathematics, Computer Science, or Statistics, or equivalent professional practical experience. They should have completed coursework in calculus, linear algebra, and probability, and have experience with programming languages such as C++ or Python.

Applicants must be able to submit proof of graduation from their current degree programs before beginning the residency. Candidates from any country may apply, and work visas will be supplied if needed. Students should also submit a resume, cover letter, transcript, and formal application. The application should demonstrate a formal interest in the field, along with any special proficiencies, awards, or skills. A formal CV should also be supplied, including a cover letter including a statement on why the applicant is qualified for the Google AI Residency.

All applications should be submitted by January 8, 2018. Interview will take place after the initial application review and running up until March 2018. Decisions will be announced in late March.

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