Senior Machine Learning Engineer (MLOPS)

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’s Technology organization is in the midst of a digital transformation that allows our employees to use world class technology to connect our products to our customers all over the world. This journey is a very exciting time for Coca-Cola and our employees are big contributors to our Success and Growth. Our large scale and complex environment offers an incredible opportunity to address challenges, enable innovative solutions to make a difference for our customers.

In this position, you will embark on a journey of leveraging vast amounts of data to transform it into actionable insights. You will aid in the development of analytics models and work under the guidance of seasoned data science professionals to drive decision-making and strategy across the organization. This is an exciting opportunity to grow in your career in data science and analytics within a supportive and innovative environment.

What You’ll Do For Us:

• Model Deployment & Operationalization: Partner with data science teams to transition machine learning models from experimentation to production environments, packaging models into robust Docker containers for scalable and reproducible deployments.
• Pipeline Automation: Build and maintain automated CI/CD pipelines for machine learning workflows (e.g., model training, evaluation, and deployment) utilizing tools like GitHub Actions. Leverage Azure Container Registry to securely manage container images and deploy scalable workloads to Azure Kubernetes Service (AKS) or Azure Container Instances (ACS).
• Utilize Azure Machine Learning and Microsoft Fabric Data Science to manage the ML lifecycle. Adapt prior experience from other cloud platforms to effectively navigate and optimize our current stack.
• Monitoring & Maintenance: Implement monitoring solutions to track model performance, data drift, and system health in production. Ensure comprehensive logging and observability for containerized model endpoints running on Kubernetes clusters. Troubleshoot and resolve operational issues as they arise.
• Data Integration: Collaborate with data engineering teams to ensure clean, reliable data pipelines (such as Medallion architectures) seamlessly feed into machine learning models.
• Engineering Best Practices: Write clean, modular, and testable code (primarily in Python) while adhering to version control best practices using Git.
• Mentor, guide, and develop junior/aspiring MLOps Engineer across the organization.
• Lead continuous career development and drive engineering excellence through performance reviews.

Qualifications& Requirements:

• 6+ years of professional experience (or equivalent strong academic/internship experience) in MLOps, Data Engineering, Software Engineering, or a related field.
• 3+ years of experience managing and scaling high-performing MLOps or data platform teams, with a focus on career development, performance management, and technical mentorship.
• Cloud ML Platforms: Hands‑on experience with at least one major cloud ML platform. While Azure ML and Microsoft Fabric are preferred, experience with AWS SageMaker, GCP Vertex AI, or similar platforms is highly acceptable.
• Programming: Strong proficiency in Python for scripting, automation, and model deployment.
• DevOps & Containerization: Familiarity with version control (Git), building CI/CD pipelines (e.g., GitHub Actions, Azure DevOps), and containerization ecosystems (Docker, Azure Container Registry, Kubernetes/AKS/ACS).
• Foundational Knowledge: A solid understanding of the machine learning lifecycle, containerized microservices architectures, and fundamental software engineering principles.

Functional

Practical experience with as many of the following as possible:

• Handles multiple competing priorities in a fast‑paced, deadline‑driven environment
• Strong attention to details and excellent problem‑solving skills
• Ability to work in a collaborative team environment
• Highly innovative, adaptable, and self‑directed
• Results‑oriented with a delivery focus
• Presentation skills: Ability to communicate technical topics to business audience.
• Be able to collaborate across other levels of the organization
• Team player who can lead a discussion to defined outcomes
• Effective Communication
• Pursuing Innovation

What We Can Do for You:

• Innovation & Technology: The ability to work with an award‑winning team that is on the cutting edge of innovation.
• Exposure to World Class Leaders: Availability to global technology leaders that will expand your network and exposure you to emerging technologies and techniques.
• Agile Work Environment: We embrace agile with management that believes in removing barriers, so you are empowered to experiment, iterate and innovate.

Our Purpose And Growth Culture:

We are taking deliberate action to nurture an inclusive culture that is grounded in our company purpose, to refresh the world and make a difference. We act with a growth mindset, take an expansive approach to what’s possible and believe in continuous learning to improve our business and ourselves. We focus on four key behaviors – curious, empowered, inclusive and agile – and value how we work as much as what we achieve. We believe that our culture is one of the reasons our company continues to thrive after 130+ years. Visit Our Purpose and Vision to learn more about these behaviors and how you can bring them to life in your next role at Coca-Cola.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class. When we collect your personal information as part of a job application or offer of employment, we do so in accordance with industry standards and best practices and in compliance with applicable privacy laws.

The Coca-Cola Company will not offer sponsorship for employment status (including, but not limited to, H1-B visa status and other employment‑based nonimmigrant visas) for this position. Accordingly, all applicants must be currently authorized to work in the United States on a full‑time basis and must not require The Coca-Cola Company's sponsorship to continue to work legally in the United States.

Pay Range: United States of America: 0 USD - 0 USD

Base pay offered may vary depending on geography, job‑related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.

Annual Incentive Reference Value Percentage: 15

Annual Incentive reference value is a market‑based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.

Location(s): United States of America

City/Cities: Atlanta

Travel Required: 00% - 25%

Relocation Provided: No

Job Posting End Date: August 29, 2026

Long‑term Incentive Reference Value Percentage: 0 - 20

Long‑term Incentive reference value is a market‑based competitive value for your role