AI / ML Engineer

Overview

Develop and operationalize production-ready machine learning systems using AI tools, cloud AI services and MLOps practices.

What you'll do

• Design, build and maintain scalable ML training pipelines.
• Deploy containerized models with Docker and serve them through FastAPI.
• Manage batch and real-time inference workflows.
• Implement CI/CD pipelines for testing, validation and deployment.
• Manage model versioning, packaging and registration using MLflow or similar tools.
• Monitor model performance, data drift and production system health.
• Collaborate across teams, make team decisions and mentor junior professionals.

What you'll need

• At least 5 years of experience in Machine Learning Operations.
• Advanced Python skills.
• Mandatory experience with MLflow and Airflow.
• Proficiency in Machine Learning Operations.
• Thorough understanding of infrastructure requirements for MLOps.
• Experience with machine learning frameworks and production model optimization.
• 15 years of full-time education.

Details

• Based at the Bengaluru office.