ML Ops Engineer (18 / 10 / 2025)

Experience - 5 - 10 yrs

Locations - Bangalore, Chennai, Mumbai, Pune, Hyderabad

Key Responsibilities

• Design, develop, and deploy machine learning models using AWS SageMaker for various business applications
• Implement end-to-end ML pipelines from data preprocessing to model serving and monitoring
• Build and maintain automated model training, validation, and deployment workflows
• Optimize model performance, scalability, and cost-effectiveness in production environments
• Create interactive ML applications and demos using Gradio for stakeholder demonstrations and user interfaces
• Develop robust Python applications for data processing, feature engineering, and model inference
• Build APIs and microservices for model serving and integration with existing systems
• Implement model versioning, A / B testing frameworks, and continuous integration / deployment practices
• ML infrastructure on AWS, including SageMaker endpoints, batch transform jobs, and processing jobs
• Monitor model performance, data drift, and system health in production environments
• Collaborate with DevOps teams to ensure reliable and scalable ML operations
• Implement security best practices for ML systems and data handling

Technical Skills