Senior Manager, Application & Machine Learning Engineer

## Senior Manager, Application & Machine Learning Engineer Apply:
US - GA
- Atlanta:
Bulgaria
- Sofia:
Full time:
Posted Yesterday:
R-145121
** Job Description

Summary:

**** Senior Manager, Application & Machine Learning Engineer
**** Role Overview
** You will build the models, optimizers and agents behind pricing, pack and promotion decisions across Coca-Cola's markets — from XGBoost and Gurobi to Lang Graph — on Databricks and Azure, working with some of the largest commercial datasets in consumer goods.  The role sits in the Product Engineering team of Coca-Cola's Global Digital Network, in a small, senior team that turns business questions from operating units and bottlers into secure, data-driven agentic solutions with executive-ready insight, increasingly delivered inside Microsoft Teams.  

This is a hands-on senior engineering role, not a people-management one. Most of your week is spent building and shipping — writing Python, training and scoring models, engineering prompts, building agents — and what you ship is used by the people who run the business.
** What You'll Do
*** Build and ship production machine learning, optimization and forecasting models on Databricks and Azure — on very large structured and unstructured datasets — that feed commercial decisions on pricing, packs and promotions.
* Design and deliver generative AI and agentic solutions — RAG, tool-calling agents and multi-agent workflows on frameworks such as Lang Graph, Semantic Kernel or Azure AI Agent Service — that give a category or brand manager a grounded, auditable answer in Teams.
* Work directly with product managers, data engineers, architects and business leaders in operating units and bottlers to turn an ambiguous question into a model, an optimization and an agent that explains its answer.
* Own your solutions in production: evaluation of model and LLM output, monitoring, MLOps and lifecycle management, and compliance with enterprise security, privacy and responsible AI standards.
* Set the engineering patterns the team reuses — code quality, testing, CI/CD, observability — so that delivery gets faster and safer with each release.
* Help shape a team that is being built now: your choices of algorithms, frameworks and practices become the standard.
** What You'll Bring
***
* Required Skills:

*** 7+ years in software, application or machine learning engineering or data science, including 3+ years delivering machine learning or AI solutions in production.
* Python at production quality: you write code that others ship and maintain.
* Applied machine learning and data science on very large datasets: model development, deployment and MLOps.
* One to two years of demonstrable prompt engineering, and at least one generative AI application delivered to production with real users.
* At least one agent built and shipped on a recognized framework (Lang Graph, Semantic Kernel, Auto Gen, OpenAI Agents SDK or Azure AI Agent Service), including retrieval-augmented generation.
* Production software practices: APIs and services, CI/CD, automated testing and observability.  
** Preferred

Skills:

*** Hands-on Microsoft Azure/AWS Databricks, including Spark / PySpark and Azure data services.
* XGBoost, forecasting and simulation models.
* Optimization modeling with Gurobi or open-source equivalents, and operations research techniques.
* Multi-agent architecture and LLM evaluation frameworks.
* Pricing, promotion, profitability, forecasting or supply chain use cases, ideally in consumer goods or for a global organization.
* R, in addition to Python.  
** Why Join
*** Scale that is hard to find: terabyte-scale commercial data from markets on four continents, and decisions that move volume and profit in the field.
* A modern stack and the mandate to use it
*…