- Build and maintain AWS SageMaker pipelines for training, validation, and deployment.
- Implement experiment tracking and model versioning.
- Automate retraining workflows.
- No less than 3 years of experience in MLOps, ML engineering or production ML system deployments
- In-depth knowledge building data pipelines for image/video preprocessing, augmentation and annotation workflows
- AWS expertise with hands-on experience in SageMaker, EC2 (GPU instances), S3 Lambda and broader AWS ecosystem for ML workloads Deep understanding CI/CD pipelines containerization Docker orchestration tools Airflow Step Functions etc
AI Pipeline Architect - Bikaner - beBeeMloper
Job title: Machine Learning Engineer
Description
Role Overview