Job Description:Role & Responsibilities:- Deploy, operationalize and maintain ML models in production, on cloud and on-premises.- Build end-to-end ML pipelines covering data prep, training, validation, deployment and monitoring.- Develop feature and data pipelines in Python and PySpark.- Work on Snowflake and/or Databricks for model development, scoring and data processing.- Implement CI/CD for ML: versioning, automated testing and release management.- Monitor model performance, data drift and system health, and drive retraining and remediation.- Work with data scientists, data engineers, architects and business stakeholders to productionize models.- Ensure security, governance, auditability and compliance for the Banking domain.- Document architectures and deployment procedures, and follow reproducibility best practices.Preferred Candidate Profile:



- Solid hands-on experience as an MLOps Engineer deploying ML models in production.- Proficient in Python and PySpark.- Working experience with Snowflake and/or Databricks.- Experience deploying models in cloud and/or on-premises environments.- Solid understanding of ML lifecycle management, model monitoring and CI/CD for ML.- Good analytical, problem-solving and communication skills.Good to have :- Banking or financial services experience.- Containerization and orchestration tools (e.g., Docker, Kubernetes).- Model registry and experiment tracking tools (e.g., MLflow).- Understanding of model risk management and banking regulations. (ref:hirist.tech)

📌 MLOps Engineer - Banking Domain (Gurugram)
🏢 Crescendo Global Leadership Hiring India
📍 Gurugram