Software Engineer - Big Data
Knewton - New York, NY

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Knewton is an education startup funded by high-profile investors including Peter Thiel and Reid Hoffman. Located in the heart of Manhattan in the Union Square area, Knewton is building the world°s most powerful adaptive learning engine, with the goal of making personalized and engaging education available to all. Knewton has been recognized as a Technology Pioneer for 2011 by the World Economic Forum in Davos and one of the top 25 best places to work by Crain ’s New York Business.

You ’ll be coding the core algorithms, models, and services that drive the Knewton Adaptive Learning Platform, the thing that generates the spot-on, highly-personalized educational recommendations that maximize each student ’s probability of success. Want to use tons of data to help figure out what students know, how they learn best, and how to help them learn more efficiently and effectively? If so, this job ’s for you!

This is an outstanding opportunity to:
  • Work with and learn from the world°s best engineers and data scientists
  • Contribute to key engineering decisions regarding technical direction of team
  • Quickly build world class consumer facing products THAT SEE DAYLIGHT
  • Become an industry luminary – we are open sourcing our projects/codebase
Engineers must have:
  • A track record of writing high-quality, elegant code
  • A willingness to learn and use Python and Java
  • The potential and desire to rise into positions of technical leadership
  • A passion for transforming education
Not required but highly desired are:
  • Experience with the Java Virtual Machine (JVM)
  • Experience in machine learning and data mining, and with the R statistical package
  • Familiarity with Amazon Web Services (AWS) and Unix
  • Experience with open-source technologies
  • Experience with big data processing using NoSQL techniques like Cassandra, Hadoop, Hive
Perks include:
  • Competitive salary and stock options
  • As much paid vacation as you need to take
  • Flexible hours
  • High-quality equipment (default setup: a Mac laptop with a giant monitor)
  • The opportunity to use cutting-edge machine learning and engineering techniques to transform and democratize education