Location: Atlanta, GA (Global HQ) - hybrid, onsite 3 days week
Estimated Travel: 0-10%
Direct Reports: None
The Global Equipment Platforms (GEP) team is seeking an exceptional and forward-thinking AI & Cloud Innovation Engineer to spearhead the exploration, prototyping, and strategic integration of cutting-edge Artificial Intelligence and advanced cloud capabilities for The Coca-Cola Company’s global fleet of 17MM+ connected equipment. Reporting to the AI & Digital Innovation Lead within GEP Digital, Data, & AI, this individual contributor role is pivotal in transforming the insights generated by our Data Scientists into tangible, deployed capabilities that reduce operating expenses, increase revenue, and provide unprecedented real-time market understanding.
You will be responsible for researching, experimenting with, and building proofs-of-concept (POCs) utilizing nascent AI technologies (e.g., advanced Generative AI applications, cutting-edge computer vision techniques, responsible AI frameworks, sophisticated AI Agents) and novel cloud architectures (e.g., edge computing for IoT, serverless AI patterns, highly distributed compute models on Azure). This role demands deep technical expertise in both AI and cloud environments, coupled with a relentless curiosity and a proven ability to translate abstract ideas into tangible, demonstrable prototypes. Your work will directly inform the future roadmap of our Unified IoT solution, ensuring we can strategically leverage breakthroughs to further reduce TCO, increase transactions, and generate unparalleled real-time insights from our KO Operating System (KOS)-powered devices across a multi-tenant global landscape.

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:

Containerization Software; Microsoft Azure Databricks; Microsoft Azure Functions; Machine Learning Operations; AI Programming; Artificial Intelligence (AI); Azure Kubernetes Service (AKS); Git; Docker (Software); Microsoft Azure Machine Learning; GitHub; Microsoft Azure DevOps; Machine Learning
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