Machine Learning Engineer

Our client is an international oil and gas company, specializing in four market sectors: Onshore Engineering & Construction, Offshore Projects & Operations, Engineering & Consulting Service, Integrated Energy Services.

The DataArt specialists will work with several projects. One of them is a project connected with the automation of internal document flow using machine learning: digitization and engineering documentation processing, change management, as well as ticket and incident management.

Another project involves upgrading the existing infrastructure, the creation of a Data Lake that will constitute a basis for building a system for generating analytical reports using machine learning.

Required Skills and Experience

• Good knowledge of Python: at least 2 years' experience in application development and debugging
• Algorithmic background: knowledge of basic algorithms and data structures
• Experience working with Machine Learning: knowledge of basic modelling and approaches to learning (linear models, GBDT, DNN, RNN, etc.)
• Knowledge of statistics, algebra, numerical methods
• Experience in development, including data analysis, formulation of hypotheses, creation of models, experimentation, and implementation of results
• Good spoken English

DataArt offers:

• Professional Development:
  - Experienced colleagues who are ready to share knowledge;
  - The ability to switch projects, technology stacks, try yourself in different roles;
  - More than 150 workplaces for advanced training;
  - Study and practice of English: courses and communication with colleagues and clients from different countries;
  - Support of speakers who make presentations at conferences and meetings of technology communities.

• The ability to focus on your work: a lack of bureaucracy and micromanagement, and convenient corporate services;

• Friendly atmosphere, concern for the comfort of specialists;

• Flexible schedule and the ability to work remotely;

• The ability to work in any of our development centers.