Machine Learning Engineer II

The Coca-Cola Company•Atlanta, GA

1d•$152,000 - $178,300

About The Position

The role is described in the posting as a senior individual-contributor position responsible for the technical vision, design, and evolution of data platforms and segmentation capabilities serving Customer and Commercial product teams. It is a hands-on technical leadership role focused on product partnership, architecture, and enabling better decisions, personalization, and measurable business outcomes rather than people management. The engineer partners with Product Managers, Designers, Tech Leads, data scientists, and business stakeholders to translate business and customer questions into durable data models and segmentation frameworks. The work includes building and operationalizing machine-learning-driven segmentation, integrating segmentation outputs into products, and defining model lifecycle standards such as monitoring, drift management, and retraining. The role defines and evolves segmentation architecture across customer and commercial data domains; designs scalable models and production-grade pipelines and services for real-time, near-real-time, and batch use cases; and promotes reusable, explainable, and consistent segmentation logic. It also emphasizes data quality, lineage, observability, reliability, privacy, consent, regulatory compliance, and responsible use of data. The position requires deep hands-on expertise with Microsoft Azure data services and Azure Data Fabric concepts. The engineer is expected to make architectural trade-offs across cost, performance, latency, accuracy, privacy, maintainability, and scalability; apply secure-by-design practices; and coordinate with enterprise architecture, cloud, and security teams. The role also provides technical guidance to senior engineers and Tech Leads without direct management responsibility, and communicates technical concepts and limitations clearly to business and external partners. The position is located in the United States, with Atlanta listed as a city, and requires 0%–25% travel. Relocation is not provided. The stated U.S. pay range is $152,000–$178,300, with a 15% annual incentive reference value. The Coca-Cola Company will not sponsor employment-based nonimmigrant visas for this position; applicants must be authorized to work in the United States full-time without requiring the company's sponsorship.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, or equivalent experience.
8+ years of hands-on experience in data platform, analytics engineering, or backend engineering roles.
Deep expertise in data modeling, segmentation strategies, and large-scale data systems.
Strong experience with cloud-native data platforms and modern data tooling.
Proven ability to partner closely with product and business stakeholders.
Demonstrated impact as a senior individual contributor on complex, cross-team initiatives.
Strong machine learning engineering experience, including using ML models to build segmentation strategies.
Deep hands-on expertise with Microsoft Azure data services and their use in large-scale, product-centric environments.
Ability to apply architectural judgment across data ingestion, storage, processing, analytics, and activation layers.
Ability to communicate technical concepts and trade-offs clearly and influence through credibility and clarity.

Responsibilities

Partner with Product Managers, Designers, and Tech Leads to co-own outcomes and participate in product discovery.
Translate business and customer questions into durable data models and segmentation frameworks.
Build machine-learning-driven segmentation strategies and operationalize them by integrating outputs into other products.
Collaborate with data scientists and manage model lifecycle standards, including monitoring, drift management, and retraining.
Define and evolve segmentation architecture across customer and commercial data domains.
Design scalable data models for real-time, near-real-time, and batch segmentation use cases.
Ensure segmentation logic is reusable, explainable, and consistent across channels and products.
Build and maintain high-quality, production-grade data pipelines and services.
Establish and maintain standards for data quality, lineage, observability, and reliability; reduce duplicated segmentation logic.
Use metrics to improve data freshness, accuracy, and usability.
Lead complex technical initiatives end-to-end through hands-on contribution and influence direction through design reviews, reference implementations, and documented standards.
Mentor senior engineers and Tech Leads through coaching and technical guidance without direct management responsibility.
Design and evolve data platform and segmentation architectures using Azure data services and Azure Data Fabric concepts.
Optimize Azure designs for cost, performance, latency, and scalability, and ensure secure-by-design implementations aligned with identity, access, encryption, and compliance controls.
Partner with enterprise architecture, cloud, and security teams and assess emerging Azure data platform capabilities for business value.
Communicate segmentation concepts, assumptions, limitations, data constraints, privacy considerations, and trade-offs to business stakeholders.
Support external partner and vendor conversations as a technical authority when needed.
Ensure segmentation complies with data privacy, consent, and regulatory requirements; work with Security, Privacy, and Legal teams to embed governance into platform design.
Advocate for responsible and ethical use of customer and commercial data.