RedditRemote · Remote - United States$230k-$322k15h ago
Coca-ColaPosted 2d ago
Senior Machine Learning Engineer (MLOPS) at Coca-Cola scores 85 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
Job Description Summary:
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 Skills:
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.Skills:
Pay Range:
United States: 143,400 - 169,300 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:
15Annual 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 AmericaCity/Cities:
AtlantaTravel Required:
00% - 25%Relocation Provided:
NoJob Posting End Date:
October 1, 2026Our 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.Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Walk me through how you've used Vertex AI in your day-to-day work.
- What are the limits of Sagemaker that you've run into, and how did you work around them?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: Ml Ops, Vertex AI, and Sagemaker. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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