Director Engineering Machine Learning Jobs (NOW HIRING)

Role Overview

The Senior Manager, Application & Machine Learning Engineer is part of the Product Engineering team within the Digital Product & Engineering organization ofCocaCola'sGlobal Digital Network and reports to the Senior Director, Engineering Excellence Lead. This role plays a critical part in advancingCocaCola'sdigital transformation by building, scaling, and operationalizing intelligent applications that embed data, artificial intelligence, and machine learning intoprioritizeddomainsacross the enterprise.

Working within an engineering excellence framework, this role partners closely with Product Managers, Product Engineers, Data Scientists, Data Engineers, Architects, and domain stakeholders to develop secure, scalable, and high-performing digital products that accelerate growth, productivity, and operational efficiency. The roleis responsible fortranslating emerging AI and machine learning capabilities into production-ready solutions that create measurable business value and support the organization's transition to a digital-first, product-centric operating model.

The ideal candidate combines modern software engineeringexpertisewith machine learning delivery experience and a passion for continuous improvement, helpingestablishbest practices, reusable engineering patterns, and operational excellence across the Digital Product & Engineering organization.

What You will do for us

• Design, develop, deploy, and support enterprise-grade applications and intelligentdigitalproducts thatleverageartificial intelligence and machine learning capabilities.

• Partner with Product Engineering, Data, Platform, and Architecture teams to embed AI-enabled functionality into products serving critical business domains.

• Drive engineering excellence by implementing modern software engineering standards, development practices, testing frameworks, and automation capabilities.

• Build, deploy, and manage machine learning solutions that can be scaled across multiple use cases, products, and business functions.

• Establish and promote reusable engineering patterns, frameworks, and components that improve product quality, maintainability, and development speed.

• Collaborate with Product Managers and business stakeholders to translate business opportunities into scalable digital solutions that deliver measurable value.

• Implement Machine Learning Operations (MLOps) practices that support model deployment, monitoring, lifecycle management, governance, and continuous improvement.

• Contribute to the Product Engineering strategy by identifying opportunities to improve application performance, developer productivity, and platform capabilities.

• Ensure solutions comply with enterprise cybersecurity, privacy, responsible AI, and architectural standards.

• Evaluate emerging technologies, engineering tools, and AI capabilities to accelerate innovation while maintaining operational stability and reliability.

• Mentor engineers and contribute to a culture of technical excellence, continuous learning, experimentation, and knowledge sharing across the Digital Product & Engineering organization.

• Support the Digital Product & Engineering organization in building scalable digital products that enable CocaCola's digital growth engine.

Requirements and Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, Information Technology, or a related technical discipline.

• 7+ years of experience in software engineering, application development, platform engineering, or digital product engineering environments.

• 3+ years of experience delivering machine learning or artificial intelligence solutions in production environments.

• Experience developing cloud-native applications using modern architectural patterns and engineering practices.

• Demonstrated expertise in application engineering, machine learning frameworks, model deployment, and production support.

• Experience implementingMLOps, CI/CD pipelines, automated testing, observability, monitoring, and deployment practices.

• Strong understanding of software design principles, APIs, microservices, distributed systems, and scalable application architectures.

• Experience collaborating within product-centric operating models and agile product delivery teams.

• Strong knowledge of engineering quality practices, code review processes, software reliability, and operational excellence principles.

• Experience integrating data, analytics, AI, and machine learning capabilities into customer-facing or enterprise digital products.

• Understanding ofresponsible AI, model governance, cybersecurity, privacy, and enterprise risk management requirements.

• Demonstrated ability to influence technical decisions and collaborate effectively within global, cross-functional teams.

• Strong communicationskills with the ability to explain complex technical concepts to both technical and non-technical stakeholders.

• Demonstrated digital fluency, AI fluency, and commitment to adopting emerging technologies that create business value.

• Experience driving continuous improvement and engineering excellence initiatives within modern technology organizations.