Job Title

Note: Looking for immediate joiners / candidates with notice period up to 15 days.What you need:Mandatory skills: Pyspark, MLFlow, MLOps, Model Lifecycle Management Orchestration (CI/CD).Strong experience in end-to-end MLOps lifecycle (deployment, monitoring, retraining).Hands-on with PySpark, Databricks, and large-scale data processing.Experience with CI/CD pipelines and ML deployment frameworks.Exposure to Docker and Kubernetes for containerized deployments.Familiarity with MLflow / model tracking and cloud platforms (AWS/Azure).What you would do:Design and maintain scalable ML pipelines for training, evaluation and deployment.Manage the end-to-end ML lifecycle using MLflow (experiments, registry, versioning).Productionise models with data scientists and ensure reliable deployment workflows.Build CI/CD pipelines for automated training, testing and release of models.Monitor model performance (drift, degradation) and implement retraining strategies.Manage cloud infrastructure and containerised workloads (Docker, Kubernetes) for scalable ML systems.