Senior Machine Learning Engineer - GUS

Grainger Businesses•Chicago, IL

12d•$134,100 - $223,500•Hybrid

About The Position

The Senior Machine Learning Engineer – GUS designs and delivers scalable, production-grade solutions that improve data-driven decision-making across the enterprise. The role leads development and automation of data pipelines, deploys machine learning and operations research models, and creates reusable tools and frameworks that help data scientists accelerate experimentation and model delivery. It collaborates with planning, product management, analytics, and other cross-functional teams to improve availability, efficiency, and business performance across operational domains. The position also guides technical execution and architecture, supports the reliability and maintainability of production machine learning solutions, and documents system designs to promote scalability and knowledge sharing.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related field.
At least 3 years of experience with production machine learning, optimization, modern data tools, and scalable engineering practices.
Experience with AWS services such as S3, ECR, and Secrets Manager.
Ability to deploy and maintain production-grade machine learning solutions using Python.
Experience applying mathematical optimization using solvers such as Gurobi.
Ability to develop web applications integrated with machine learning and ERP systems.
Knowledge of operations research and optimization modeling.
Experience with database technologies such as Snowflake or DuckDB and SQL for data querying.
Experience with containerization tools including Kubernetes and Docker.
Understanding of machine learning concepts such as time series forecasting and clustering.
Knowledge of software engineering best practices, including version control and CI/CD tools such as GitHub and GitHub Actions.
Experience automating workflows using orchestration tools such as Astronomer or Airflow.
Experience building and supporting solutions within the Databricks platform.
Experience with machine learning frameworks and libraries such as PyTorch and scikit-learn.

Nice To Haves

Master's degree in a related technical field or equivalent practical experience.

Responsibilities

Lead development of scalable, automated processes for large-scale data analysis, model training, validation, and deployment.
Oversee implementation and continuous improvement of machine learning and operations research models in collaboration with data scientists, partnering cross-functionally to align work with business needs.
Design and maintain robust ETL pipelines and automate critical system operations to support reliable data flow and model performance.
Build internal tools and web applications that enable stakeholders to interact effectively with machine learning and ERP systems.
Evaluate and integrate emerging technologies to drive innovation and align solutions with strategic goals.
Ensure production-grade reliability and maintainability of deployed machine learning solutions using software engineering and DevOps best practices.
Mentor and guide team members in technical execution, architecture decisions, and career development.
Create and maintain architectural diagrams and documentation supporting system design, scalability, and knowledge sharing.

Benefits

Medical, dental, vision, and life insurance coverage beginning on the first day of employment.
Six free sessions each year with a licensed therapist.
18 annual paid time off days for full-time employees, prorated based on employment start date.
Six company holidays per year.
6% company contribution to a 401(k) Retirement Savings Plan each pay period, with no employee contribution required.
Employee discounts.
Tuition reimbursement.
Student loan refinancing.
Free access to financial counseling, education, and tools.
Maternity support programs and nursing benefits.
Up to 14 weeks of paid leave for birth parents and up to 4 weeks of paid leave for non-birth parents.