DevOps MlOps

Own and manage every aspect in the MLOps life cycle for our AI-based automatic sports highlights generation platform. Design, implement and maintain our whole ML infrastructure, from research to production and from model training to data engineering. Automate and innovate workflows such as serving and training pipelines for multidisciplinary ML algorithms including Computer Vision, NLP and Data Science. Build and maintain CI/CD pipelines, releases and Source Code workflows. 4+ years experience as an MLOps engineer, DevOps engineer or similar fields Experience in a complex, large-scale, high-uptime production cloud environment. Core understanding of Linux OS, Docker Components, Kubernetes. Experience with CI/CD pipelines for distributed production systems Experience with python scripting. Work experience with Terraform. Understanding of AI and machine learning fundamentals, concepts and frameworks - advantage. Working with MLOps platforms such as Experiment Tracking, Model Registry, feature Store - Advantage (e.g ClearML , W&B, Aws Sagemaker) Working with Azure Cloud in high-scale production environment - Advantage