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.
· 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
Would be an advantage.
Excellent communication skills in English, both verbal and in writing.