Intermediate Machine Learning Engineer - Supply Chain Forecast Engine
About The Position
Join Publix’s Supply Chain Forecast Engine team to build forecasting solutions for store, warehouse, and ATM systems. These solutions provide forecasts used for product and ATM cash replenishment, helping ensure the right amounts are available for customers. The role develops and maintains machine learning and forecasting solutions, builds scalable ML and data pipelines, and supports deployment and production performance. It involves partnering with data scientists, cloud engineers, and business teams while applying software engineering practices to create reliable, maintainable, and testable ML solutions. The position is hybrid in Lakeland, Florida. Candidates must live within a commutable distance or be willing to relocate there. Candidates advancing in the interview process must participate in at least one onsite interview at the Lakeland campus.
Requirements
- Bachelor’s degree in computer science or another analytical discipline, or equivalent experience.
- At least 3 years of software, data, or machine learning engineering experience, including strong experience developing production solutions with Python and SQL.
- At least 1 year of experience with Databricks and Spark/PySpark.
- At least 1 year of experience deploying and supporting machine learning models in an enterprise production environment.
- Experience building data or ML pipelines involving large datasets and Declarative Asset Bundles (DABs).
- Experience with Delta Lake and Azure.
- Experience with time-series and demand-based forecasting models.
- Knowledge of MLOps, CI/CD, automated testing, model monitoring, and version control.
- Must reside within a commutable distance of Lakeland, Florida, or be willing to relocate there.
Responsibilities
- Develop and maintain machine learning and forecasting solutions using Python and SQL.
- Build scalable ML and data pipelines using Databricks, Spark/PySpark, and Delta Lake.
- Develop automated deployment processes using Databricks Asset Bundles (DABs) and CI/CD.
- Partner with data scientists, cloud engineers, and business teams to produce demand forecasting models.
- Monitor model and pipeline performance and troubleshoot production issues.
- Apply software engineering practices to create reliable, maintainable, and testable ML solutions.
Benefits
- Hybrid flexibility, with remote work and onsite collaboration.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
