Senior MLOps Engineer - Production ML Leader

The Coca-Cola Company; Atlanta (GA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical benefits

Bonus / incentive program

Job summary

The Coca-Cola Company is seeking an experienced MLOps professional to transform data into actionable insights, deploy models in production, and lead a growing ML/AIOps team in Atlanta. You will collaborate with data engineering to ensure clean data pipelines and mentor junior engineers while advancing engineering excellence and scalable solutions.

You will leverage Azure ML, containerized microservices, and modern CI/CD practices to deliver robust ML systems.

Qualifications

• 6+ years of professional experience in MLOps, Data Engineering, or a related field.
• 3+ years of experience managing and scaling MLOps or data platform teams.
• Hands‑on experience with at least one major cloud ML platform (Azure ML, AWS SageMaker, GCP Vertex AI).
• Strong proficiency in Python for scripting, automation, and deployment.
• Experience building CI/CD pipelines and containerization (GitHub Actions, Docker, Kubernetes).
• Foundational knowledge of ML lifecycle and microservices architectures.

Responsibilities

• Deploy and operationalize ML models in production with Dockerized packaging.
• Build and maintain CI/CD pipelines for ML workflows (training, evaluation, deployment).
• Monitor model performance, data drift, and system health in production.

Skills

Python

GitHub Actions

Cloud platforms

Mentorship

Team leadership

Tools

Docker

Kubernetes

Azure Container Registry

Azure ML

Microsoft Fabric Data Science

Job description

The Coca-Cola Company is seeking an experienced MLOps professional to transform data into actionable insights, deploy models in production, and lead a growing ML/AIOps team in Atlanta. You will collaborate with data engineering to ensure clean data pipelines and mentor junior engineers while advancing engineering excellence and scalable solutions.

You will leverage Azure ML, containerized microservices, and modern CI/CD practices to deliver robust ML systems.