Backend MLOps Engineer

• Develop robust and scalable backend services with FastAPI to enable AI-driven features
• Design and implement MLOps infrastructure to support model training, deployment, and lifecycle management
• Configure and manage AWS services including SageMaker, EventBridge, RDS, IAM, and S3
• Build and maintain containerized applications using Docker and Kubernetes for scalable deployment
• Establish CI/CD pipelines to automate deployment, monitoring, and system security
• Work closely with ML engineers and product teams to ensure end-to-end system reliability and seamless integration

Must Have:

• Minimum 5 years of experience with FastAPI and MLOps
• Strong proficiency in Python programming
• Proven experience developing backend services using FastAPI
• Hands-on experience with Docker for containerization
• Practical experience working with Kubernetes for orchestration
• Solid knowledge of AWS services: IAM, S3, RDS, SageMaker, and EventBridge
• Strong understanding of CI/CD tools such as GitHub Actions, Jenkins, or equivalent
• Bachelor’s degree in Computer Science, DevOps, or a related technical field
• English proficiency at an intermediate level

Nice to Have:

• Familiarity with infrastructure-as-code tools such as Terraform or AWS CloudFormation