Lead ML & Data Platforms Engineer

The Coca-Cola Company; Atlanta, Northern (GA, KY); Hybrid; USD 171,000 - 198,000; Full time

Benefits offered by this job

Medical benefits

Relocation provided

Job summary

The Coca-Cola Company in Atlanta is seeking a Senior Data/Machine Learning Engineer to lead end-to-end ML capabilities within product teams. You will set technical direction for ML systems, with a focus on data foundations, governance, and scalable pipelines.

You will partner with product, design, data science, and platform teams to frame problems, build models, deploy them, monitor performance, and iterate with a strong emphasis on reliability and impact.

Qualifications

• 6+ years of experience in machine learning engineering, data engineering, or software engineering with ML/data systems leadership.
• Strong Python (production quality) and SQL, with CI/CD practices.
• Experience shipping ML systems in production with monitoring and retraining strategies.

Responsibilities

• Technical direction for product ML domain: problem framing, approach selection, evaluation strategy, and iteration.
• Build data foundations: event definitions, feature tables, training/serving consistency.
• Deploy and operate models in production with monitoring, drift detection, and cost considerations.
• Develop APIs/services exposing model predictions to enterprise apps.
• Mentor engineers and establish reusable ML + data patterns across teams.

Skills

Strong programming in Python

SQL proficiency

Data engineering

ML system design

MLOps

Model deployment

Model monitoring

Cross-functional collaboration

Python & SQL production practices

Cloud platforms

Education

Bachelor’s degree in CS/Engineering or related field

Tools

Airflow

Dagster

Spark

dbt

Docker/Kubernetes

PyTorch/TensorFlow

SQL tooling

Job description

The Coca-Cola Company in Atlanta is seeking a Senior Data/Machine Learning Engineer to lead end-to-end ML capabilities within product teams. You will set technical direction for ML systems, with a focus on data foundations, governance, and scalable pipelines.

You will partner with product, design, data science, and platform teams to frame problems, build models, deploy them, monitor performance, and iterate with a strong emphasis on reliability and impact.