The Coca-Cola Company is seeking an AI & Cloud Innovation Engineer to transform the insights generated by Data Scientists into tangible, deployed capabilities that reduce operating expenses, increase revenue, and provide unprecedented real-time market understanding for their global fleet of 17MM+ connected equipment.
Requirements
- 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).
Responsibilities
- Design, develop, and maintain robust, scalable MLOps pipelines for deploying, monitoring, retraining, and versioning machine learning models, AI Agents, and computer vision algorithms.
- Implement automated CI/CD processes for AI artifacts, ensuring rapid and reliable deployment of models into production environments (e.g., Azure ML, Azure Kubernetes Service).
- Collaborate with Lead Data Engineers and Digital Technology Solutions (IT) to provision, configure, and optimize cloud-based AI infrastructure (e.g., GPU clusters, specialized compute instances) on Azure.
- Integrate AI capabilities seamlessly into existing GEP applications and platforms, including remote equipment management tools, content management systems, marketing solutions, and analytics dashboards.
- Research, prototype, and engineer solutions for emerging AI technologies, including the operationalization of AI Agents for autonomous decision-making and advanced computer vision algorithms for real-time insights from equipment.
- Implement comprehensive monitoring, logging, and alerting for deployed AI models, tracking performance metrics (e.g., latency, throughput, error rates), model drift, and data quality issues in production.
- Proactively identify bottlenecks and optimize the performance and cost-efficiency of AI inference and retraining pipelines.
Other
- 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.
- 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.
- Estimated Travel: 0-10%
- Direct Reports: None
