Senior Machine Learning Engineer

Grainger Corporate Services LLC; Chicago (IL); Hybrid; USD 134,000 - 224,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Paid time off

401(k) match

Tuition reimbursement

Employee discounts

Maternity/paternity benefits

Job summary

Grainger Corporate Services LLC in Chicago, IL is seeking an experienced ML/OR engineer to design scalable, production-grade data solutions. You will lead automated pipelines for data analysis, model training, validation, deployment, and build reusable tools for experimentation and delivery.

You will collaborate with cross-functional teams to align analytics with business needs, implement ETL pipelines, leverage AWS, Python, SQL, and modern data tools, and mentor teammates on architecture and

Qualifications

• Bachelor’s degree in CS/Engineering or related field (required).
• Master’s degree in related technical field or equivalent practical experience (preferred).
• 3+ years of production ML, optimization, modern data tools, and scalable engineering practices (required).
• Experience with AWS services including S3, ECR, Secrets Manager.

Responsibilities

• Design and deliver scalable, production-grade ML and OR solutions.
• Lead automated data pipelines for data analysis, model training, validation, and deployment.
• Collaborate cross-functionally to align analytics with business needs.

Skills

AWS

Python

Gurobi

SQL

Kubernetes

Docker

Databricks

PyTorch

scikit-learn

GitHub

GitHub Actions

Airflow

Astronomer

S3

ECR

Secrets Manager

Snowflake

DuckDB

SQL (time series)

Education

Bachelor’s degree

Master’s degree

Tools

Gurobi

Snowflake

DuckDB

Job description

Drive scalable, production-grade machine learning and operations research solutions in a hybrid role in Chicago.

Responsibilities

• Lead the development of scalable automated workflows 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.
• Partner cross-functionally to ensure model and analytics efforts align with business needs.
• Design and maintain robust ETL pipelines and automate critical system operations for reliable data flow and model performance.
• Build internal tools and web applications enabling stakeholders to interact with ML and ERP systems.
• Evaluate and integrate emerging technologies to support innovation and strategic alignment.
• Ensure production-grade reliability and maintainability of deployed ML solutions using software engineering and DevOps best practices.
• Mentor and guide team members on technical execution, architecture decisions, and career development.
• Create and maintain architectural diagrams and documentation to support system design, scalability, and knowledge sharing.

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 production ML, optimization, modern data tools, and scalable engineering practices (required).
• Demonstrated experience with AWS services including S3, ECR, and Secrets Manager.
• Ability to deploy and maintain production-grade machine learning solutions using Python.
• Apply mathematical optimization using solvers such as Gurobi.
• Develop and support web applications integrated with machine learning and ERP systems.
• Apply knowledge of operations research and optimization modeling.
• Use database technologies such as Snowflake and DuckDB with SQL for data querying.
• Work with containerization tools including Kubernetes and Docker.
• Understand machine learning concepts including time series forecasting and clustering.
• Follow software engineering best practices including version control and CI/CD (for example, GitHub, GitHub Actions).
• Automate workflows using orchestration tools such as Astronomer or Airflow.
• Build and support solutions within the Databricks platform.
• Use machine learning frameworks and libraries such as PyTorch and scikit-learn.

Technologies

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

Benefits

• Medical, dental, vision, and life insurance plans with coverage starting on day one
• 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

Location and Work Model

• Chicago, IL (hybrid)

Compensation

• Anticipated base pay range: $134,100.00 – $223,500.00 (per year)
• Eligible for an incentive target of up to 10% based on individual and company performance objectives (terms subject to change)
• Not eligible for visa sponsorship

Position Details

• Design and deliver scalable, production-grade solutions that enhance data-driven decision-making across the enterprise.
• Lead development of robust automated data pipelines, deploy advanced ML and operations research models, and create reusable tools and frameworks to accelerate experimentation and model delivery.
• Collaborate with cross-functional teams including planning, product management, and analytics to improve availability, efficiency, and overall business performance across operational domains.