As a Machine Learning Operations Engineer, you will work separately and with the team to design, develop, deploy, and manage ETL data pipelines and machine learning models. You will assist in different areas of project management, including client projects and internal initiatives.
You are someone with:
3+ years relevant work experience with building and automating data analytics and Machine Learning (ML) pipelines
Good understanding of ML and AI concepts. Hands-on experience in ML model development.
Experience in operationalization of Machine Learning projects (MLOps) using at least one of the popular frameworks or platforms (e.g. AWS Sagemaker, Google AI Platform, DataRobot).
Strong experience in Python used both for ML and automation tasks.
Database and programming languages experience and data manipulation and integration skills using SQL, Oracle, Hadoop, NoSQL Databases, or similar tools
Experience with Kubernetes and the ecosystem of Cloud Native tools.
Ability to work with data with significant ambiguity, develop creative approaches to analytical problems, and interpret data and results from a business/industry perspective
Strong oral and written communication skills
Minimum Bachelor degree in Computer Science, Software Engineering or related field
Experience with AWS platform is a plus
Project management experience is a plus
