Senior MLOps Engineer: Lead Production ML at Scale

The Coca-Cola Company; Atlanta (GA); Hybrid; USD 143,000 - 169,000; Full time

Job summary

The Coca-Cola Company’s Technology organization is transforming how we leverage data and deploy ML across our global business. We are seeking an experienced Senior ML Engineer (MLOps) to partner with data science teams and own deployment, monitoring, and scalable containerized services.

You will lead CI/CD pipelines, work with Azure ML, AKS, and adopt best practices, while mentoring peers. Strong Python, cloud experience, and a passion for reliable, production-grade ML are essential.

Qualifications

• 6+ years in MLOps or related fields.
• 3+ years leading MLOps or data platform teams with mentorship.
• Hands-on with at least one major cloud ML platform (Azure ML preferred; AWS SageMaker/GCP Vertex AI acceptable).
• Strong Python for scripting, automation, and deployment.
• Familiar with CI/CD and containerization (Git, GitHub Actions, Docker, Kubernetes).
• Solid understanding of ML lifecycle and containerized microservices.

Responsibilities

• Deploy and operationalize ML models in production with containerized services.
• Build and maintain CI/CD pipelines for model training, evaluation, and deployment.
• Leverage Azure ML and Fabric Data Science; adapt to other cloud platforms.
• Monitor model performance and data drift; ensure observability on Kubernetes.
• Mentor engineers and drive engineering excellence across teams.

Skills

MLOps leadership

Python

Cloud ML Platforms

Docker

Kubernetes

CI/CD

Mentorship

Tools

Azure ML

GitHub Actions

Azure Kubernetes Service

Kubernetes

Azure Container Registry

AKS

Azure ML

Microsoft Fabric Data Science

Job description

The Coca-Cola Company’s Technology organization is transforming how we leverage data and deploy ML across our global business. We are seeking an experienced Senior ML Engineer (MLOps) to partner with data science teams and own deployment, monitoring, and scalable containerized services.

You will lead CI/CD pipelines, work with Azure ML, AKS, and adopt best practices, while mentoring peers. Strong Python, cloud experience, and a passion for reliable, production-grade ML are essential.