Machine Learning Engineer II

**Job Description Summary:**The Senior Manager, Software Engineer, Data Platform & Segmentation is a individual contributor accountable for the technical vision, design, and evolution of data platforms and segmentation capabilities that power Customer and Commercial product teams operating under a modern Product Operating Model.This role functions as a hands-on technical engineer with 3 to 6 years of experience on data and machine learning engineering.The role emphasizes deep technical expertise, product partnership, and architecture, rather than people management.**Core Accountabilities**Product Model & Discovery Partnership* Partner closely with Product Managers, Designers, and Tech Leads to co-own outcomes, not just data assets.* Participate actively in product discovery to ensure segmentation strategies are technically feasible, scalable, and analytically sound.* Translate business and customer questions into durable data models and segmentation frameworks.Data Platform & Segmentation Architecture* Analyze and integrate structured and unstructured data from enterprise platforms, customers, and external data providers.* Build scalable data preparation and feature engineering pipelines for ML applications.Machine Learning* Develop predictive and recommendation models using appropriate statistical and machine learning techniques.* Evaluate and select appropriate approaches based on each use case, including: Classification and regression Ranking and recommendation Clustering and segmentation Time-series and forecasting Gradient-boosting and tree-based models Deep learning and transformers Computer vision Embeddings, vector search and RAG* Build reliable training and inference pipelines for batch and near-real-time use cases.* Develop APIs and services that expose model predictions to web, mobile, CRM, Salesforce, and other enterprise applications.* Establish rigorous model evaluation, testing and validation practices.Engineering Execution & Data Quality* Build and maintain high-quality, production-grade data pipelines and services.* Ensure strong standards for data quality, lineage, observability, and reliability.* Implement MLOps pipelines covering training, testing, versioning, deployment and model lifecycle management.* Monitor production models for model performance, data quality, drift and other operational issues.* Implement appropriate retraining, rollback and model versioning strategies.* Troubleshoot issues across data pipelines, models, inference services, APIs, and production environments.* Create reusable ML components and patterns that can support multiple Transaction Growth use cases.* Participate in architecture reviews, code reviews and engineering design discussions.**Microsoft Azure Data Platform & Fabric Expertise*** Design and evolve segmentation and data platform architectures leveraging Azure Data Fabric concepts, ensuring interoperability, governance, and reuse across domains.* Apply strong architectural judgment across core Azure data products, including data ingestion, storage, processing, analytics, and activation layers.* Optimize designs across cost, performance, latency, and scalability, using Azure-native capabilities and patterns.* Ensure secure-by-design implementations aligned with Azure identity, access, encryption, and compliance controls.* Partner with enterprise architecture, cloud, and security teams to ensure Azure data platform decisions align with broader enterprise strategy while preserving team autonomy.* Stay current on Azure data platform evolution and proactively assess new capabilities for business value, not novelty.**Business Partnership & Communication*** Serve as a trusted technical partner to Customer and Commercial stakeholders.* Communicate segmentation concepts, assumptions, and limitations in clear business language.* Proactively surface data constraints, privacy considerations, and trade-offs to enable informed decisions.* Support external partner and vendor conversations as a technical authority when needed.**Governance, Privacy & Compliance*** Ensure segmentation approaches comply with data privacy, consent, and regulatory requirements.* Collaborate with Security, Privacy, and Legal teams to embed governance into platform design - not bolt it on later.* Advocate for responsible and ethical use of customer and commercial data.**Success Measures*** Segmentation capabilities measurably improve customer engagement and commercial outcomes.* Reduced duplication and inconsistency in segmentation logic across products.* Improved data quality, freshness, and trustworthiness.* Faster time-to-insight and activation for product teams.* Platforms and models that scale with growth while controlling cost and risk.**Required Experience & Capabilities*** Bachelor's degree in Computer Science, Engineering, Data Science, or equivalent experience.* 3+ years of hands-on experience in data platform, analytics engineering, or backend engineering roles.* Strong programming experience with Python or common data and ML libraries.* Experience developing production machine learning models using frameworks such as scikit-learn, PyTorch, TensorFlow, XGBoost, or equivalent.* Strong understanding of supervised and unsupervised learning, model selection, feature engineering and statistical modeling.* Experience preparing large datasets for machine learning, including cleansing, transformation, feature generation and quality validation.* Strong SQL skills and experience working with large enterprise datasets.* Experience designing training, evaluation and inference pipelines.* Experience deploying machine learning models into production environments.* Practical understanding of MLOps, including experiment tracking, model versioning, CI/CD, automated testing, deployment and monitoring.* Experience developing or integrating APIs and services used for model inference.* Strong software engineering practices including modular design, source control, code review, automated testing and production debugging.* Experience working with cloud-based data and ML platforms.* Ability to assess multiple modeling approaches and select the simplest solution capable of meeting the business objective.* Strong communication skills and the ability to collaborate with product managers, business stakeholders, software engineers and data teams.The Coca-Cola Company will not offer sponsorship for employment status (including, but not limited to, H1-B visa status and other employment-based nonimmigrant visas) for this position. Accordingly, all applicants must be currently authorized to work in the United States on a full-time basis and must not require The Coca-Cola Company's sponsorship to continue to work legally in the United States.**Skills:****Pay 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:**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.***Location(s):**United States of America**City/Cities:**Atlanta**Travel Required:**00% - 25%**Relocation Provided:**No**Job Posting End Date:**October 14, 2026**Our 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. #J-18808-Ljbffr