The Position

We need a passionate Machine Learning Ops Engineer to help us in discovering and implementing state-of-the-art solutions for our Machine Learning projects to enable rapid experimentation, increase accuracy of our models and ensure high quality of our products.

Job Responsibilities:

· Research and implement MLOps tools, frameworks and platforms for our Data Science projects.

· Work on a backlog of activities to raise MLOps maturity in the organization.

· Proactively introduce a modern, agile an d automated approach to Data Science.

· Conduct internal training and presentations about MLOps tools’ benefits and usage.

Required experience and qualifications:

· Wide experience with Kubernetes is a must have.

· Experience in operationalization of Data Scienc e projects (MLOps) using at least one of the popular frameworks or platforms (e.g. Kubeflow, AWS Sagemaker, Google AI

Platform, Azure Machine Learning, DataRobot, DKube, Notebook , Dataiku ( Will train ) ). ·

Good understanding of ML and AI concepts. Hands -on experience in ML model development.

· Proficiency in Python used both for ML and automation tasks. Good knowledge of Bash and Unix command line toolkit.

· Experience in CI/CD/CT pipelines implementation.

· Experience with cloud platforms

Preferably AWS

Would be an advantage.

Excellent communication skills in English, both verbal and in writing.