Senior Engineer-Devops, Machine Learning Operations

About the role

Infrastructure team provides various services including automation, observability, cloud/server/network architectures, CICD, infrastructure as code, database administration, incident management, vendor management, security and compliance, and acquiring new skills. These services help to improve efficiency, reduce errors, and ensure fast and reliable application releases while maintaining security and compliance.

What you'll do

• Design and maintain end-to-end MLOps pipelines for data ingestion, feature engineering, model training, deployment, and monitoring
• Productionize ML/GenAI services, collaborating with data scientists on model serving and workflow optimization
• Implement monitoring, alerting, and observability to reduce MTTR and ensure production reliability
• Manage data/feature stores and search infrastructure for scalable ML inference
• Automate CI/CD for ML models and infrastructure with governance and security compliance

What you need

• 7–13 years in devops & cloud
• Machine learning
• AWS
• CI/CD
• Linux
• Shell scripting
• Python
• Any graduate

Good to have

• MLOps
• Elasticsearch
• FastAPI
• Spring Boot
• DynamoDB
• SQL