The Coca-Cola Company
US - GA - Atlanta
ML Engineering
Posted 14 hours ago
Verified open on Oct 9, 2026 · posted today
Job Description Summary:
Role Overview
The Senior Manager, Application and Machine Learning Engineer – Fuelight, is a key member of the Product Engineering team within the Digital Product & Engineering organization of the Global Digital Network and reports to the Senior Director, Engineering Excellence Lead.
This role is responsible for advancing Fuelight, Coca‑Cola’s strategic resource allocation and investment optimization product, which enables more informed marketing, trade, and commercial investment decisions through advanced analytics, machine learning, scenario planning, and AI-enabled decision support. Fuelight is designed as an always-on, globally scalable digital product that integrates diverse business data, predictive models, optimization capabilities, and decision intelligence into a unified experience for teams across the Coca‑Cola System.
The role combines modern software engineering, machine learning engineering, and AI product development expertise to build scalable digital capabilities that help business users understand performance drivers, evaluate investment tradeoffs, simulate future scenarios, and optimize resource allocation decisions. Working closely with Product Managers, Data Scientists, Data Engineers, Business Science teams, and Operating Unit stakeholders, this leader will help transform advanced analytical models into trusted, enterprise-grade applications that drive business adoption and measurable value realization.
What You will do for us
Design, develop, and enhance Fuelight applications that enable investment optimization, resource allocation, scenario planning, and decision intelligence across the Coca‑Cola System.
Build and operationalize machine learning capabilities that support predictive modeling, investment recommendations, performance evaluation, and optimization outcomes.
Partner with Engineering teams to translate analytical models into production-grade digital products.
Develop scalable application architectures that support Fuelight’s continued expansion across markets, operating units, bottling partners, and business processes.
Create intuitive user experiences that enable business users to interpret model outputs, evaluate tradeoffs, and make informed decisions with confidence.
Implement MLOps capabilities that enable model deployment, monitoring, governance, retraining, observability, and lifecycle management.
Develop AI-enabled features that improve user productivity, accelerate insight generation, and support data-driven decision making.
Integrate complex data products, forecasting capabilities, optimization engines, and business-rule frameworks into a unified product experience.
Support explainable AI and model transparency initiatives, including features that help users understand drivers, assumptions, recommendations, and outcomes.
Collaborate with stakeholders across Marketing, Finance, Commercial, Franchise, Revenue Growth Management, and Bottler organizations to deliver product enhancements aligned to business priorities.
Establish engineering standards, reusable frameworks, and best practices that improve quality, reliability, maintainability, and development efficiency.
Contribute to Fuelight’s long-term product vision by evaluating emerging technologies, AI capabilities, and engineering approaches that strengthen the platform’s competitive advantage.
Ensure solutions comply with enterprise architecture, cybersecurity, privacy, responsible AI, and governance requirements.
Support product adoption and scale by partnering with global teams to continuously improve performance, usability, and business value realization.
Requirements and Qualifications
Bachelor’s degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, Machine Learning, Information Systems, or a related technical discipline.
8+ years of experience in software engineering, application engineering, digital product development, or enterprise technology delivery.
4+ years of experience developing, deploying, and supporting machine learning or artificial intelligence solutions in production environments.
Experience building cloud-native, data-intensive applications using modern engineering practices and scalable architectures.
Strong expertise in machine learning engineering, predictive modeling, optimization techniques, and decision-support applications.
Experience operationalizing machine learning solutions through MLOps, CI/CD pipelines, model monitoring, automated testing, and deployment automation.
Strong understanding of APIs, microservices, distributed systems, event-driven architectures, and enterprise application integration.
Experience developing products that leverage advanced analytics, forecasting, optimization, recommendation engines, or scenario planning capabilities.
Ability to translate complex analytical concepts into intuitive user-facing applications and digital experiences.
Experience working within product-centric and Agile delivery models in cross-functional global teams.
Knowledge of responsible AI, model explainability, governance frameworks, cybersecurity requirements, and data privacy principles.
Strong collaboration skills with the ability to work effectively across engineering, data science, product management, and business functions.
Demonstrated digital fluency, data literacy, and AI fluency, with an ability to evaluate and adopt emerging technologies that create business value.
Strong communication, problem-solving, and stakeholder management capabilities.
Experience supporting globally scaled digital products serving multiple markets, customer groups, or business functions is preferred.
Skills:
Budget Management, Communication, Data Analytics, DOT Regulations, Group Problem Solving, JDA (Inactive), Microsoft Office, Microsoft Power Business Intelligence (PBI), Oracle Transportation Management, SAP Manufacturing Execution (SAP ME), Supply Chain, Tableau (Software), Transportation Logistics, Transportation Management Systems (TMS), Transportation PlanningPay Range:
United States: 152,000 - 178,300 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 16, 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.Not ready to apply?
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This role is classified as ML Engineering.
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$200k - $281k is the middle 50% of disclosed salaries, measured from 248 live ML Engineering postings on this board. Roughly two thirds of postings disclose nothing, so this describes the ones that do, not the whole market.
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