Description

You will design and maintain backend services powering MLOps capabilities for the end-to-end machine learning lifecycle.

Responsibilities

• Develop backend systems, REST APIs, and data pipelines to drive MLOps functionality.
• Own complete delivery cycles from initial requirements through to go-live.
• Drive architectural decisions and collaborate with data science teams to fine-tune machine learning algorithms.
• Mentor junior engineers and document project workflows and best practices.

Required Skills

• 7+ years of industry experience, preferably within enterprise environments.
• Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, or a related field.
• Proficiency with backend frameworks: Spring, Flask, FastAPI, and Hibernate.
• Hands-on experience with Hasura, Swagger, and SonarQube.
• Experience building and maintaining CI/CD pipelines.
• Knowledge of Kubernetes, Docker, and Docker Compose.
• Experience with cloud platforms (AWS, Azure, or GCP).
• Understanding of event pipelines, pub/sub, data streaming, and distributed caching.
• Familiarity with ELK stacks and ESB architectures.

Key Skills

Education

Any graduate