Jobs → Engineering → MLOps Engineer

About the Role We are seeking a Senior MLOps Engineer to build, deploy, and optimize scalable machine learning platforms and production ML systems. This role focuses on end-to-end ML lifecycle management, automation, monitoring, governance, and real-time model deployment. Key Responsibilities • Build and maintain scalable ML platforms and production systems • Automate model training, testing, deployment, rollback, and retraining • Implement model versioning, experiment tracking, registries, and governance • Develop feature stores and scalable data pipelines • Monitor model performance, data quality, drift, and system reliability • Build batch and real-time inference solutions • Support security, compliance, auditability, and model risk controls • Collaborate with Data Science, Data Engineering, and Software Engineering teams Requirements • 10+ years of experience in MLOps or ML engineering • Strong expertise in AWS SageMaker, Python, and SQL • Experience with production ML deployment and monitoring • Knowledge of CI/CD/CT pipelines • Familiarity with feature stores and scalable data pipelines • Understanding of model versioning, experiment tracking, and governance • Experience with batch and real-time inference solutions • Ability to support security, compliance, auditability, and model risk controls • Collaboration skills with Data Science, Data Engineering, and Software Engineering teams