Senior Manager, Application & Machine Learning Engineer

The Coca-Cola Company • Atlanta, GA

6d • $152,000 - $178,300

About The Position

The Senior Manager, Application & Machine Learning Engineering is a hands-on individual contributor in The Coca-Cola Company's Technology organization. The role builds and deploys machine learning, optimization, and AI solutions supporting commercial decision-making across the global business. Using large-scale enterprise datasets, the engineer develops forecasting models, predictive analytics, optimization engines, and agentic AI applications for decisions involving pricing, promotions, revenue growth, profitability, and operational performance.

The position spans traditional machine learning, generative AI, retrieval-augmented generation (RAG), and agentic AI. It partners with product managers, engineers, architects, and business stakeholders to turn complex business questions into scalable production solutions. Success requires a strong machine learning foundation and practical experience building AI applications that are deployed, monitored, maintained, and continuously improved in production.

The role owns solutions throughout their lifecycle, including development, deployment, monitoring, evaluation, and ongoing improvement. It also establishes and applies engineering practices for secure, reliable, maintainable, observable, and scalable AI applications. The role is based in Atlanta, Georgia, with 0%–25% travel. Relocation is not provided. The Coca-Cola Company will not sponsor employment-based visas; applicants must already be authorized to work full-time in the United States without company sponsorship.

Requirements

• At least 7 years of experience in software engineering, machine learning engineering, AI engineering, data science, or related technical disciplines.
• At least 3 years of experience delivering AI and machine learning solutions in production environments.
• Experience developing enterprise decision-support solutions for business and operational decision-making.
• Production Python development experience.
• Production experience with Microsoft Azure and Databricks.
• Experience with Azure Data Services and Spark/PySpark.
• Experience with machine learning technologies such as XGBoost and optimization platforms such as Gurobi or comparable tools.
• Experience working with large-scale enterprise datasets, including structured and unstructured data.
• Experience designing, developing, and supporting cloud-native applications, distributed systems, APIs and microservices, data-intensive applications, and data warehousing solutions.
• Experience with MLOps, including model deployment, monitoring, lifecycle management, and observability.
• Experience with CI/CD pipelines, automated testing, deployment automation, and operational readiness.
• Experience developing, deploying, and supporting production machine-learning models for forecasting, prediction, recommendations, optimization, or other business decision support.
• Experience building generative AI applications using LLMs, prompt engineering, and RAG.
• Experience building and deploying AI agents and agentic workflows using frameworks such as LangGraph, Semantic Kernel, AutoGen, Azure AI Agent Service, OpenAI Agents SDK, or similar.
• Ability to translate business requirements into technical solutions.
• Ability to communicate technical decisions and model outcomes to technical and non-technical stakeholders.
• Ability to manage competing priorities and recommend practical delivery approaches in ambiguous environments.
• Must be currently authorized to work full-time in the United States and not require The Coca-Cola Company's sponsorship to continue working legally in the United States.

Responsibilities

• Design, develop, deploy, and support machine learning, optimization, and AI solutions for commercial and operational decision-making.
• Build predictive, recommendation, forecasting, and optimization models using large-scale structured and unstructured datasets.
• Develop generative AI applications using LLMs, prompt engineering, RAG, and agentic AI frameworks.
• Build AI agents and decision-support experiences that provide grounded, explainable, and actionable recommendations.
• Own solutions through development, deployment, monitoring, evaluation, and continuous improvement.
• Monitor model and agent performance, identify drift, evaluate outputs, and improve solution effectiveness.
• Ensure solutions meet enterprise standards for security, privacy, reliability, and responsible AI.
• Write production-quality Python code and reusable engineering components.
• Build APIs, microservices, and distributed services that support AI and machine learning applications.
• Implement automated testing, CI/CD pipelines, deployment automation, observability, and operational-readiness practices.
• Establish engineering patterns that improve delivery speed, quality, maintainability, and scalability.
• Explain technical concepts and model outputs to technical and non-technical audiences.
• Translate business requirements into scalable technical solutions.
• Resolve ambiguity, recommend practical approaches, and influence stakeholders through technical expertise.

Benefits

• A full range of medical, financial, and/or other benefits is offered, dependent on the position.
• Annual incentive reference value of 15%, representing the market-based target value for the role.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed