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MLOps engineer

Vilnius Job No. r00116360 Full-time

Job Description

MLOps is a set of management techniques for the deep learning or production ML lifecycle, formed from machine learning or ML and operations or Ops. These include ML and DevOps methods, as well as data engineering processes for deploying and maintaining machine learning models in production.



  • Competitive salary 3300 - 5350 EUR gross
  • Flexible vacation + health & travel insurance + relocation
  • Work from home, flexible working hours
  • Work with Fortune 500 companies from different industries all over the world
  • Skills development and training opportunities, company-paid certifications
  • Opportunities to advance career
  • An open-minded and inclusive company culture

Key responsibilities:

  • Design and implement cloud solutions, build MLOps on cloud (AWS, Azure, or GCP)
  • Build CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Circle CI, Airflow or similar tools
  • Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality
  • Data science models testing, validation and tests automation
  • Communicate with a team of data scientists, data engineers and architect, document the processes

Required Qualifications:

  • Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS, MS Azure or GCP)
  • Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes, OpenShift
  • Programming languages like Python, Go, Ruby or Bash, good understanding of Linux, knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc.
  • Ability to understand tools used by data scientist and experience with software development and test automation
  • Fluent in English, good communication skills and ability to work in a team

Desired Qualifications:

  • Bachelor’s degree in Computer Science or Software Engineering
  • Experience in using AWS, MS Azure or GCP services.
  • Good to have any associate Cloud Certification

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