Senior ML Engineer: Production & Automation Lead

W.W. Grainger, Inc.; Chicago (IL); On-site; USD 134,000 - 224,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

PTO and holidays

401(k) retirement plan

Job summary

W.W. Grainger, Inc. is seeking a Senior Machine Learning Engineer – GUS to design and deliver scalable, production-grade ML/data-pipeline solutions that boost data-driven decisions across the enterprise.

You will lead automated data analysis, model training, ETL pipelines, and internal tooling while collaborating with planning, product management, and analytics. This role emphasizes reliability, scalability, and cross-functional impact.

Qualifications

• Bachelor's degree in CS/engineering or related field.
• 3+ years production ML and scalable engineering.
• Experience with AWS (S3, ECR, Secrets Manager).
• Python for production ML.
• Experience with SQL and databases.

Responsibilities

• Leads development of scalable, automated data analysis processes for large-scale ML
• Oversees ML/OR models with data scientists and cross-functional teams
• Designs and maintains ETL pipelines and automates critical system operations
• Builds internal tools and web apps for ML/ERP interaction
• Assesses emerging technologies to drive innovation and align with goals
• Ensures production-grade reliability and DevOps practices for ML solutions
• Mentors team members on execution, architecture, and growth
• Creates architecture diagrams and docs to support scalability and knowledge sharing

Skills

Python

AWS

Gurobi

SQL

Docker

Kubernetes

PyTorch

scikit-learn

Time series forecasting

CI/CD

Education

Bachelor's Degree in Computer Science, Engineering, or related field

Master's Degree Related technical field or equivalent practical experience

Tools

Snowflake

DuckDB

Databricks

Job description

W.W. Grainger, Inc. is seeking a Senior Machine Learning Engineer – GUS to design and deliver scalable, production-grade ML/data-pipeline solutions that boost data-driven decisions across the enterprise.

You will lead automated data analysis, model training, ETL pipelines, and internal tooling while collaborating with planning, product management, and analytics. This role emphasizes reliability, scalability, and cross-functional impact.