We develop, implement, and improve recommendation systems for various Yandex services with hundreds of millions of DAU and thousands of RPS, processing terabytes of data in real-time. To enhance user experience, we work on ML infrastructure for 50+ services and hundreds of developers. You can become part of a team whose results impact users every day.

We offer: * Variety of projects and development of skills and experience in the field of recommendations across different domains * Opportunity to improve services and see the results of your work * Team with a strong technical background * Opportunity to implement your own ideas * Advanced infrastructure for rapid deployment and improvement of recommendations

What tasks await you

• Full-cycle ML development from idea to implementation
• Experiments with data analysis, user behavior patterns, and various recommendation schemes
• Training and implementation of neural network SotA models
• Working with large-scale projects where machine learning plays a key role

We expect that you

• Have a deep understanding of ML principles and are ready to apply this knowledge to solving real-world problems
• Are genuinely interested in implementing changes that significantly impact user services
• Know C++ or want to learn it
• Are proficient in Python

Will be a plus

• Experience with recommendation systems or NLP
• Expert in C++
• Experience with transformer models
• Experience with PyTorch or other deep learning frameworks

Working conditions

• Formal employment
• Flexible schedule: we do not monitor arrival or departure times, the main thing is to complete tasks
• Extended voluntary health insurance program including dental, check-ups, etc.
• High total compensation, bonuses every six months
• Opportunity to participate in Yandex educational programs, lectures, meetups
• Work in a team of talented experts from whom you can learn a lot
• Culture of openness and mutual support
• Opportunity to quickly see the results of your work and create services used by millions of people