MLOps Engineer job description:
Hands on experience with Azure Machine Learning, Databricks, and Azure DevOps.
Strong knowledge of MLOps, including data drift, model drift, and model performance monitoring using MLflow.
Expert in DevOps practices, including CI CD pipelines and automation.
In-depth experience with Kubernetes and containerized applications.
Familiarity with data engineering concepts and ETL processes.
Experience managing data science projects and collaborating with cross-functional teams.
Proficient in Python, Bash, or PowerShell for scripting and automation.
Hands on experience with public cloud platforms, preferably Azure.
Strong background in managing AI/ML environments and optimizing performance using MLflow.