About the job
Artificial Intelligence – Machine Learning Engineer Internship Fall 2021
LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, discover opportunities, and gain insights. Our global reach means we get to make a direct impact on the world’s workforce in ways no other company can. We’re much more than a digital resume – we transform lives through innovative products and technology.
We are looking for applied research engineer interns and scientist interns to work on our massive semi-structured text, graph and user activity data sets. Build highly scalable, highly performant social graph engines, state-of-the-art full-text search engines, and platforms for recommendation and applied data analytics. You will utilize data mining, information retrieval, machine learning and perfect your strong systems orientation skills.
– Work with BIG data, crunching millions of samples for statistical modeling, data mining, recommendation, or search relevance solutions
– Write production quality code and influence the next generation of LinkedIn’s systems
– This is a full-time fall internship role based in Sunnyvale, CA, San Francisco, CA, New York, NY, or Toronto, ON.
-This internship will take place Fall 2021
– Currently pursuing a B.S., M.S., or Ph.D in computer science, statistics, mathematics, electrical engineering, machine learning, or related technical field and returning to the program after the completion of the internship
– Hands-on experience with machine learning, data mining, or statistics
– Expected to complete degree by December 2022 or earlier
– Excellent programming skills
– Experience or desire to learn Hadoop
– Strong command of algorithms and data structures
– Expertise in clustering, collaborative filtering, and classification techniques (Naïve Bayes, SVM, NN, Boosting Methods, etc.)
As part of the application process for this role, after an initial qualifications review, candidates are required to successfully complete the HackerRank online code challenge. Instructions for completion of the code challenge will be sent to you if your application is selected to move forward in the process.
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