Location: Atlanta, GA (Global HQ) - hybrid, onsite 3 days/week
Estimated Travel: 0-10%
Direct Reports: None
The AI Engineer & Transformation for Global Equipment Platforms (GEP) will be critical in operationalizing and scaling AI capabilities across Coca-Cola’s 17MM+ connected equipment fleet. This role is responsible for designing, building, and maintaining robust MLOps pipelines and production infrastructure for machine learning models, AI Agents, and computer vision solutions, bridging the gap between data science research and reliable, large-scale deployment to drive significant business impact.
You will play a hands-on role in deploying AI across cloud and edge environments (including KOS-enabled devices), ensuring high performance, reliability, and cost-effectiveness. Your work will directly contribute to reducing equipment Total Cost of Ownership (TCO), increasing transactions, and providing unprecedented real-time market insights that eliminate the “fog of war” for Coca-Cola’s global operations, bottlers, and OEM partners. This role demands a strong engineering mindset, deep expertise in cloud-native AI services (Azure preferred), and a passion for turning cutting-edge AI research into tangible business value.

REQUIRED EXPERIENCE & QUALIFICATIONS:

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related quantitative field. Master’s or Ph.D. preferred.
• 7+ years of hands-on experience in AI/ML engineering, MLOps, or productionizing machine learning models in cloud environments.
• Expert-level proficiency in designing, building, and operating production-grade AI/ML pipelines on Microsoft Azure (e.g., Azure Machine Learning, Azure Kubernetes Service, Azure Functions, Azure Databricks).
• Strong software engineering background with extensive experience in Python, including developing robust, production-quality code and APIs.
• Proficiency with containerization technologies (Docker) and orchestration platforms (Kubernetes).
• Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and deploying models trained with these frameworks.
• Solid understanding of cloud infrastructure concepts, networking, and security best practices relevant to AI deployments.
• Experience with Git and CI/CD tools (e.g., Azure DevOps, GitHub Actions).
• Familiarity with IoT, telemetry data, and embedded systems (exposure to KOS or similar OS is a plus).
• Proven ability to work independently and drive technical projects from conception to production.

COMPETENCIES:

• Engineering Excellence: Possesses deep software engineering principles and applies them rigorously to build robust, scalable, and maintainable AI solutions.
• AI Vision & Execution: Translates strategic AI concepts into practical, deployable systems, bridging research with real-world application.
• Problem Solver & Innovator: Tackles complex technical challenges in AI deployment, consistently seeking and implementing innovative solutions.
• Collaborative Integrator: Works effectively across diverse technical teams (Data Science, Data Engineering, IT) and with business stakeholders to ensure seamless AI integration.
• Results-Driven & Accountable: Focuses on delivering tangible business value through deployed AI, taking ownership of the end-to-end operational success of solutions.
• Continuous Learner: Stays abreast of the rapidly evolving AI landscape and proactively adopts new technologies and best practices.

SKILLS:

Microsoft Azure Databricks; PyTorch; Microsoft Azure Functions; Machine Learning Operations; Docker (Software); Azure Kubernetes Service (AKS); GitHub; Python (Programming Language); Containerization Software; Tensorflow; Artificial Intelligence (AI); AI Programming; Git; Microsoft Azure Machine Learning; Microsoft Azure Internet of Things (IOT); IoT Applications
All persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form (Form I-9) upon hire.
Pay Range:$131,000 - $153,000
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