Minimum of 5-7 years of experience in ML engineering with large-scale production systems.  Strong experience with Azure cloud computing and containerization technologies (like Docker, Kubernetes). 

 Experience in API creation and deployments (for ex. Fast API, flask etc.)  Experience with Python/OOPs programming languages and data science frameworks like (Pandas, Numpy, TensorFlow, Keras, PyTorch, sklearn). 

 Knowledge of DevOps tools such as Git, Jenkins, Sonar, Nexus is must.  Building python wheels and debugging build process.  Data pipeline building and debugging (by creating and following log traces).  Basic knowledge of DevOps practices.  Concepts of Unit Testing and Test-Driven development.  Experience with Databricks and its ecosystem is highly preferred