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.

Benefits:

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