The LinkedIn Content Understanding team leverages large volumes of data and state-of-the-art machine learning techniques to understand what our 500+ million members read and write about on linkedin.com. We blend expertise in machine learning, natural language processing, software engineering, evaluation and human judgment. We apply this expertise to develop and deploy topic extraction, document classification, named entity recognition, entity linking and information extraction technologies at scale. Our work benefits the LinkedIn feed experience, personalized content recommendation, ads relevance and more.
Interns on our team may work on areas such as: graph visualisation, graph browsing and editing, machine learning, and natural language processing.
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 internship role that will take place between May - September 2019
- 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
- Expected to complete degree by July 2021 or earlier
- Hands-on experience with machine learning, data mining, or statistics
- 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.)
If interested, please apply at: https://www.linkedin.com/jobs/view/1076631699/