Intermediate Machine Learning Engineer - Supply Chain Forecast Engine

Hybrid work in Lakeland, FL with the flexibility to focus remotely and collaborate onsite when it matters. You will contribute to Publix’s Supply Chain Forecast Engine team by building forecasting solutions for store, warehouse, and ATM systems, backed by a culture that supports autonomy, creativity, and continuous learning.

This role supports operational efficiency through reliable automation and scalable data workflows, helping ensure forecasting technology integrates cleanly into day-to-day business operations. If you enjoy turning machine learning into maintainable, production-ready systems, you’ll work across model development, data pipelines, monitoring, and deployment.

What you’ll do

• Develop and maintain machine learning and forecasting solutions using Python and SQL.
• Build scalable ML and data pipelines with Databricks, Spark/PySpark, and Delta Lake.
• Create 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 for supply chain needs.
• Monitor model and pipeline performance, then troubleshoot production issues to maintain stability.
• Apply software engineering practices to deliver reliable, maintainable, and testable ML solutions.

Core technologies

• Python, SQL
• Databricks
• Spark, PySpark
• Delta Lake
• Databricks Asset Bundles (DABs)
• CI/CD

Location and work model

Hybrid (Lakeland, FL): To support the hybrid work model, candidates must reside, or be willing to relocate, within a commutable distance of Lakeland, FL.

Enjoy the best of both worlds: collaborate in person and innovate remotely.

Interview process

Candidates selected to advance in the interview process will be required to participate in at least one onsite interview at the Publix Lakeland, FL campus.