Senior Machine Learning Engineer (MLOPS)

• →

  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. 

• 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. 

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 

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.