Senior Machine Learning Engineer

Grainger Corporate Services LLC is hiring a Senior Machine Learning Engineer to design and deliver scalable, production-grade machine learning and operations research solutions. Based in Chicago, IL on a hybrid schedule, this role leads automated data pipelines and model deployment while building reusable tools and frameworks that help teams ship models faster and reliably.

In partnership with data scientists and cross-functional stakeholders, you will focus on improving availability, efficiency, and business performance across enterprise operational domains.

Position overview

The Senior Machine Learning Engineer (GUS) designs and delivers scalable, production-grade solutions that strengthen data-driven decision-making across the enterprise. The role leads development and automation of robust data pipelines, deploys advanced machine learning and operations research models, and creates reusable tooling that accelerates experimentation and model delivery.

You will collaborate with teams including planning, product management, and analytics to drive improvements in availability, efficiency, and overall business performance across diverse operational domains.

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 with data scientists, partnering cross-functionally to align 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 help stakeholders interact with ML and ERP systems effectively.
• Evaluate and integrate emerging technologies to drive innovation and align solutions with strategic goals.
• Ensure production-grade reliability and maintainability of deployed ML solutions using best practices in software engineering and DevOps.
• Mentor and guide team members in technical execution, architecture decisions, and career development.
• Create and maintain architectural diagrams and documentation to support system design, scalability, and knowledge sharing across teams.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field (required).
• Master’s degree in a related technical field or equivalent practical experience (preferred).
• 3+ years of production machine learning, optimization, modern data tools, and scalable engineering practices (required).
• Experience with AWS services including 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.
• Experience developing web applications integrated with machine learning and ERP systems.
• Knowledge of operations research and optimization modeling.
• Working knowledge of database technologies (e.g., Snowflake, DuckDB) and SQL for data querying.
• Experience working with containerization tools including Kubernetes and Docker.
• Understanding of machine learning concepts such as time series forecasting and clustering.
• Familiarity with software engineering best practices including version control and CI/CD (e.g., GitHub, 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 including PyTorch and scikit-learn.

Technologies

• AWS: S3, ECR, AWS Secrets Manager
• Python, Gurobi
• Snowflake, DuckDB, SQL
• Kubernetes, Docker
• GitHub, GitHub Actions
• Astronomer, Airflow
• Databricks
• PyTorch, scikit-learn

Compensation and incentive

• Base pay range: USD 134,100 - 223,500 per year
• Incentive target: eligible for up to 10%, based on individual and company performance objectives (per the current incentive program terms, which are subject to change)
• Visa sponsorship: not eligible

Benefits

• Medical, dental, vision, and life insurance plans with coverage starting on day one of employment
• 6 free sessions each year with a licensed therapist
• 18 paid time off (PTO) days annually for full-time employees
• 6 company holidays per year
• 6% company contribution to a 401(k) Retirement Savings Plan each pay period, no employee contribution required
• Employee discounts
• Tuition reimbursement
• Student loan refinancing
• Free access to financial counseling, education, and tools
• Maternity support programs
• Nursing benefits
• Up to 14 weeks paid leave for birth parents
• Up to 4 weeks paid leave for non-birth parents