Senior MLOps Engineer (AWS SageMaker & Airflow)

We are looking for an experienced MLOps Engineer to join our cloud and AI engineering team. This role is ideal for professionals with strong hands-on experience in AWS SageMaker–centric ML workflows and Apache Airflow–based orchestration.

Requirements

• Design, build, and maintain end-to-end MLOps pipelines using AWS SageMaker
• Develop and manage Airflow DAGs for ML workflow orchestration (training, validation, deployment, retraining)
• Automate model training, evaluation, versioning, and deployment
• Implement CI/CD pipelines for ML workflows and model releases
• Manage model lifecycle, including experimentation, deployment, monitoring, and retraining
• Integrate data ingestion and feature engineering workflows with ML pipelines
• Monitor model performance, data drift, and pipeline reliability
• Collaborate closely with Data Scientists, Data Engineers, and DevOps teams
• Ensure security, scalability, and cost optimization across ML infrastructure