MLOps Engineer (Python & Cloud)

Role Overview

We are looking for an MLOps Engineer to help bring machine learning models into production and keep them reliable, measurable, and easy to maintain.

Key Responsibilities

• Build and maintain workflows for model deployment, versioning, and monitoring.
• Automate machine learning processes using CI/CD practices.
• Work with data scientists and engineers to move models from experimentation to production.
• Monitor model performance and troubleshoot issues with production workflows.
• Document processes and improve the reliability of the ML infrastructure.

Required Qualifications

• Hands-on experience deploying or maintaining machine learning models in production.
• Strong Python skills.
• Experience with CI/CD, Git, and containerization using Docker.
• Experience with at least one cloud platform: AWS, Azure, or GCP.
• Familiarity with model tracking, versioning, and monitoring practices.

Nice to Have

• Experience with MLflow, Vertex AI, SageMaker, or a comparable platform.
• Experience with Kubernetes or automated model retraining.
• Experience supporting LLM applications in production.