Пропустити навігацію EPAM

Senior Machine Learning Engineer Tbilisi, Georgia or Remote

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Senior Machine Learning Engineer Description

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.


We are looking for a Senior Machine Learning Engineer who can design and implement standardized processes and technology capabilities for building, deploying and operationalizing ML systems rapidly and reliably. To provide leadership in defining and implementing strategies and tools, working with internal and external stakeholders.

Half of the time is dedicated to the hands-on analysis of data science initiatives, plans, and ML-powered products. In contrast, the other half is spent building data and modelling pipelines, tools and applications to automate that process.

What You’ll Do

  • Work with Data Scientists to understand what they are working on, analyze the work from a machine learning engineering point of view and list a roadmap of what needs to be done to bring ML artefacts into life: guiding practices on how to improve, helping with a preliminary ML system design and anticipating of consequent Product changes, advising what the team should look for the project, implementing of some hypotheses (YOLO model, an algorithm from a whitepaper, etc.)
  • Participate in the code review process
  • Participate in the code review process
  • Design and build efficient and reproducible ML pipelines: producing features and anything needed to iterate over a model (feature selection, hyperparameter tuning, validation, etc.)
  • Schedule and operate model in a production data pipeline
  • Design and build ML pipeline end to end to promote ML artefacts into production
  • Analyze and communicate model performance
  • Write clean and tested code that can be maintained and extended by other software engineers
  • Keep up to date on relevant technologies and frameworks and propose new ones that the team could leverage
  • Have some vision on an ML system design to fill in the gaps
  • Build a framework (coordination between teams, DevOps, Data Engineers, QA, MLE, DS)

What You Have

  • Expertise in Python and its ecosystem
  • Machine learning, software engineering and distributed computing basics
  • Experience with DBMS and different data models (relational, columnar, document, etc.)
  • Competency in building HTTP-based APIs for distributed systems
  • Experience with machine learning tools such as Pandas, Numpy, Scikit-Learn, TensorFlow, PyTorch, DeepAR, Prophet, Catboost, XGBoost, Spark, PySpark and tasks such as Time Series forecasting, Computer Vision, Recommendation Systems
  • Understanding how web applications are built and organized
  • Experience with continuous integration and continuous development

We Offer

  • Innovative solutions delivery to the world’s digital changes
  • Experience exchange with colleagues all around the world
  • Opportunities for self-realization
  • Unlimited access to LinkedIn learning solutions
  • Friendly team and enjoyable working environment
  • Engineering, corporate and social events
  • Social package: professional & soft skills trainings, medical & family care programs, sports
  • Free English classes
  • Flexible working schedule