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.