MLOps Engineer

• Strong experience (min. 2 years) in Kubernetes is a must have
• Proficiency in Python (preferably used both for ML and automation tasks). Good knowledge of Bash and Unix command line toolkit

• Experience in operationalization of Data Science 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)
• Good understanding of ML and AI concepts. Hands-on experience in ML model development.
• Experience in CI/CD/CT pipelines implementation.
• Experience with cloud platforms - preferably AWS
• Communication skills in English

PROJECT DESCRIPTION: 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.

• 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 and automated approach to Data Science