Intern researcher (Machine Learning)

MoscowData analysis, Machine learningJunior specialist
Yandex Research invites beginners to an internship in our team. We offer a unique opportunity to engage in world-level applied and theoretical research, publish your results at leading conferences and contribute to the high-tech services of Yandex: e.g., modern computer vision technologies, dialogue systems, neural machine translation, self-driving cars and more. If you are interested in algorithms and machine learning, if you follow the latest research papers (from conferences like ICML, NeurIPS, ICLR, CVPR, ACL, KDD, ICCV, ECCV, EMNLP, ect.), and believe in yourself as a beginner researcher, we will be happy to talk with you. We promise attention to your ideas, a comfortable office in central Moscow, a productive environment, and a friendly and open working atmosphere.

You will be engaged in:

  • development of new technologies;
  • conducting experiments to verify your scientific hypotheses;
  • writing papers describing new results;
  • presenting your results on the top-tier international conferences.


  • technical education with good training in mathematics and algorithms (complete or incomplete; senior university students are welcome);
  • programming skills in Python or C ++ sufficient for conducting experiments;
  • desire to regularly read and analyze academic publications;
  • desire to pursue a scientific career.

The following advantages will also be taken into account (non-exhaustive list):

  • high level of mathematical culture;
  • basic knowledge in at least one of the following areas: Machine Learning, Computer Vision, Natural Language Processing, Game or Auction Theory;
  • experience in writing academic articles;
  • experience in writing technical texts of any kind in English;
  • experience in participating in international scientific competitions, such as Internet Mathematics, KDD Cup, Kaggle competitions;
  • experience of work or study in foreign universities or research laboratories;
  • experience in developing and working with large data (starting from one billion records);
  • teamwork experience.