Senior DevOps Engineer (MLOps Retraining)
Kharkiv, Ukraine
5 днів тому


Transforming the way thousands of global organizations do business by developing the most innovative technologies and processes in Big Data, Internet of Things (IoT), Data Science, and Experience Design.

We are one of the largest teams in Eastern Europe that stood at the origins of Data Science, so you will get tons of experience while working with the best talents in the field.

In a Data Science Center of Excellence, you will have a chance to contribute to a wide range of projects in different areas and technologies.

We are looking for a person who is inspired by data, analytics, and AI as much as we are, and who wants to grow with us!


A skilled DevOps Engineer ready to switch career direction to MLOps and pass an intensive 2-month practical retraining at SoftServe!

A candidate should demonstrate such experience and abilities as

  • Python beyond scripting
  • Setting up CI / CD pipelines
  • Profound knowledge of Docker and Kubernetes
  • Strong cloud expertise in AWS, GCP, or Azure
  • Workflow orchestration platforms such as Airflow
  • Infrastructure as Code such as Terraform
  • Design of monitoring and logging (principles, best practices, tools)
  • Participation in ML projects in any roles
  • Interest in AI / ML, a basic understanding of Data Science techniques
  • Bright problem solving and presentation skills
  • This experience will make you stand out

  • Setting up and configuring Spark / DataBricks clusters
  • Setting up and configuring data stores such as Postgres, Redis, or MongoDB
  • Linux administration and Shell Scripting
  • Knowledge of configuration management systems like Ansible
  • Giving presentations, workshops, and others

    An exciting possibility to

  • Communicate with stakeholders to identify use cases, gather requirements, and set up expectations
  • Guide Engineering and Data Science teams through ML systems production lifecycle
  • Educate Product teams on best practices for putting ML systems in production
  • Collaborate with Data Science teams on model operationalization strategies
  • Cooperate closely with Product teams to deliver and operate ML systems
  • Design and implement end-to-end production pipelines for ML solutions
  • Support and continuously enhance ML software infrastructure : CI / CD, data stores, cloud services, network configuration, security, and system monitoring
  • Design and implement automated deployment and integration of ML models
  • Set up scalable monitoring systems for data pipelines and ML models
  • Maintain ML pipelines in production

  • Operationalize our clients’ AI solutions by leveraging best practices in DevOps, Machine Learning, and Solution Architecture
  • Maintain synergy of Data Scientists, DevOps team, and ML Engineers to build infrastructure, set up processes, productize machine learning pipelines, and integrate them into existing business environments
  • Participate in international events
  • Get certifications in cutting-edge technologies
  • Have the possibility to work with the latest modern tools and technologies on different projects
  • Have access to strong educational and mentorship programs
  • Communicate with the world-leading companies from our logos portfolio
  • Work as a consultant on different projects with a flexible schedule
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    Клацнувши по кнопці "# кнопка", я даю згоду neuvoo на обробку моїх даних та надсилання сповіщень електронною поштою, як це детально описано в Політиці конфіденційності neuvoo. Я можу будь-коли відкликати свою згоду або скасувати підписку.