Вакансия Senior Machine Learning Engineer

5 вакансий
Специализация: Data Science
Уровень: Senior
Опыт: 5 лет
Уровень английского: Upper-Intermediate
Город: Минск
Режим работы: Полный день
Размер команды: 13+
Размер компании: 50
Возможна удалённая работа: Да

InData Labs is a data science firm and AI-powered solutions provider with its own R&D center. Our main focus lies in machine learning and deep learning solutions, as well as building high-load data processing systems.

Currently, we are looking for a Senior Machine Learning Engineer who will be a part of the general-purpose data science team with a focus on recommender systems for natural language content.

In this position, you will often communicate with a customer and consult both technical and non-technical team members regarding questions within your domain of machine learning and data-driven solutions.

Responsibilities:

  • Understand business needs and restrictions and offer appropriate technical solutions in the domain of data-driven applications, describe qualities and limitations of proposed approaches to non-technical people.
  • Work mainly with numerical and textual data, state data collection and labelling requirements and recommendations.
  • Design and implement rule-based and machine learning solutions, including data preparation; selection, training, validation and optimization of machine learning models; realistic data-grounded evaluation of created solutions.
  • Integrate data preprocessing, model training and inference into general data processing pipelines.
  • Research new tools, papers, etc. in the machine learning area.

Requirements:

  • Strong knowledge and deep understanding of
    • Main concepts and stages of the modelling process (validation scheme, regularization, overfitting and generalization, data leaks, feature selection, etc.)
    • Сlassical machine learning (linear models, decision trees, ensembles for classification and regression tasks, clustering and dimensionality reduction)
    • Recommender systems fundamentals (content-based, collaborative filtering, hybrid, evaluation process)
  • Understanding main problems and concepts of modern Natural Language Processing
  • Hands-on experience with Python scientific and ML-related libraries (scipy, numpy, pandas, scikit-learn, xgboost/lightgbm/catboost, matplotlib/seaborn, PyTorch/TensorFlow, etc.)
  • Good Python programming skills and ability to write code not only in Jupyter Notebooks
  • Basic knowledge and skills of algorithms and data structures, relational databases and SQL
  • Ability and desire to convert raw business requests into strictly formulated machine learning tasks, data gathering (data labelling, if needed) requirements
  • At least 3-year experience in machine learning or data-driven applications development
  • Good spoken and written English (at least B2)

Would be a plus:

  • Experience with Linux-based operating systems, Git and Docker
  • Production experience in developing recommender systems
  • Experience in software engineering, deployment and integration with data delivery systems and other components, building microservices, providing APIs for models access, web scraping
  • Experience with ML stack of Microsoft Azure, AWS or Google Cloud
  • Data visualization and presentation skills
  • Experience in Deep Learning with applications to any data domain
  • Experience in data labelling process setup using third-party or self-made labelling tools
  • Participation in ML competitions (Kaggle, etc), contribution to ML-related public projects
  • Masters, PhD, or equivalent experience in Mathematics, Computer Science or Computational Linguistics.

What we offer:

  • Competitive compensation;
  • Flexible schedules available;
  • Generous benefits package from day one of employment: medical coverage, sport reimbursement, English classes, bonuses for special occasions (birthday, wedding, etc.), paid vacations and sick leaves;
  • Immense training and growth opportunities.

Join our team of world-class data scientists and data engineers, and challenge yourself with some of the most pressing data science and engineering tasks of modern times!

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