Machine Learning Engineer


от 250 000 до 400 000 ₽

Местоположение и тип занятости

Полный рабочий деньМожно удаленно


Создаем системы риск-менеджмента, online-трейдинга на торговых биржах, CRM, а также Web и mobile приложения для торговли

Описание вакансии

Условия работы

We are looking for a Machine Learning Engineer to join our growing efforts in data science, machine learning, and R&D. You’ll be part of the Data Products team, working with our Data Scientists, Data Engineers and Developers to architect data pipelines, support machine learning research, and bring machine learning features to production.

What you’ll be doing:

  • working with our Engineering teams, you will help build production features that leverage our machine learning technologies
  • you will help develop infrastructure for rapid machine learning feature prototyping, deployment, and evaluation with customers
  • working on our Data Products team, you will build and optimize data lakes and feature stores to feed research projects
  • gain experience in ML Ops by architecting, optimizing, monitoring, and deploying machine learning systems to production
  • learning and applying best practices for ETL and batch processing of database, log, image, and HTML data.
  • learning about machine learning techniques on unstructured web page data, such as attention models, NLP techniques and ConvNets
  • participate in large-scale project planning and stakeholder education

A little bit about you:

  • 5 or more years of experience working with MLOps
  • you have experience deploying machine learning models in production, and with production architecture, monitoring and logging
  • you can communicate clearly and empathetically with developers, product managers, and UX designers to explain the abilities and limitations of ML systems
  • programming with Python and the associated data science/machine learning packages (e.g. scikit-learn, pandas, xgboost, numpy, scipy)
  • management of databases (we principally use MySQL, Postgres, and DynamoDB)
  • cloud infrastructure, preferably AWS, especially S3, and CloudFormation
  • running services in Docker environments
  • an understanding of web technologies, including APIs (we use REST and GraphQL)
  • Linux administration and command line tools
  • Agile development, version control, and code review processes
  • Big Data ETL (we principally use PySpark)


We offer:

  • ability to influence project technologies;
  • possibility of career growth;
  • insurance, corporate English, sports compensation;
  • friendly team without hierarchy inside;
  • corporate events;
  • competitive remuneration