About this role
Summary: Designs and delivers scalable, production-grade data pipelines and machine learning and operations research models. Builds reusable tools and frameworks that help data scientists accelerate experimentation and model delivery.
Work Location Type: Hybrid
Req Number 336299
About Grainger
W.W. Grainger, Inc., is a leading broad line distributor with operations primarily in North America, Japan and the United Kingdom. At Grainger, We Keep the World Working® by serving more than 4.5 million customers worldwide with products and solutions delivered through innovative technology and deep customer relationships. Known for its commitment to service and award-winning culture, the Company had 2024 revenue of $17.2 billion across its two business models. In the High-Touch Solutions segment, Grainger offers approximately 2 million maintenance, repair and operating (MRO) products and services, including technical support and inventory management. In the Endless Assortment segment,http://Zoro.com offers customers access to more than 14 million products, andhttp://MonotaRO.com offers more than 24 million products. For more information, visit[www.grainger.com.](http://www.grainger.com)
Compensation
The anticipated base pay compensation range for this position is $134,100.00 – $223,500.00. This role is eligible for an incentive target of up to 10 %, based on the achievement of individual and company performance objectives in accordance with the current terms of the incentive program which are subject to change.
Position is not eligible for visa sponsorship.
Rewards and Benefits
With benefits starting on day one, our programs provide choice and flexibility to meet team members' individual needs, including:
- Medical, dental, vision, and life insurance plans with coverage starting on day one of employment and 6 free sessions each year with a licensed therapist to support your emotional wellbeing.
- 18 paid time off (PTO) days annually for full-time employees (accrual prorated based on employment start date) and 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 and free access to financial counseling, education, and tools.
- Maternity support programs, nursing benefits, and up to 14 weeks paid leave for birth parents and up to 4 weeks paid leave for non-birth parents.
For additional information and details regarding Grainger’s benefits, please click on the link below:
https://experience100.ehr.com/grainger/Home/Tools-Resources/Key-Resources/New-Hire
Grainger Benefits
The pay range provided above is not a guarantee of compensation. The range reflects the potential base pay for this role at the time of this posting based on the job grade for this position. Individual base pay compensation will depend, in part, on factors such as geographic work location and relevant experience and skills.
The anticipated compensation range described above is subject to change and the compensation ultimately paid may be higher or lower than the range described above.
Grainger reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion at any time, consistent with applicable law.
Position Details
The Senior Machine Learning Engineer – GUS designs and delivers scalable, production-grade solutions that enhance data-driven decision-making across the enterprise. This role leads the development and automation of robust data pipelines, deploys advanced machine learning and operations research models, and creates reusable tools and frameworks that enable data scientists to accelerate experimentation and model delivery. The position collaborates with cross-functional teams—including planning, product management, and analytics—to drive improvements in availability, efficiency, and overall business performance across diverse operational domains.
You Will
- Leads the development of scalable, automated processes for large-scale data analysis, model training, validation, and deployment.
- Oversees the implementation and continuous improvement of machine learning and operations research models in collaboration with data scientists, while partnering cross-functionally to ensure alignment with business needs.
- Designs and maintains robust ETL pipelines and automate critical system operations to support reliable data flow and model performance.
- Builds internal tools and web applications that enable stakeholders to interact with ML and ERP systems effectively.
- Evaluates and integrates emerging technologies to drive innovation and align solutions with strategic goals.
- Ensures production-grade reliability and maintainability of deployed ML solutions using best practices in software engineering and DevOps.
- Mentors and guides team members in technical execution, architecture decisions, and career development.
- Creates and maintains architectural diagrams and documentation to support system design, scalability, and knowledge sharing across teams.
You Have
- Bachelor's Degree Computer Science, Engineering, or a related field required
- Master's Degree Related technical field or equivalent practical experience preferred
- 3+ years Production ML, optimization, modern data tools, and scalable engineering practices required
- Demonstrates experience with AWS services such as S3, ECR, and Secrets Manager.
- Deploys and maintains production-grade machine learning solutions using Python.
- Applies mathematical optimization using solvers like Gurobi.
- Develops web applications integrated with machine learning and ERP systems.
- Applies knowledge of operations research and optimization modeling.
- Utilizes database technologies (e.g., Snowflake, DuckDB) and SQL for data querying.
- Works with containerization tools including Kubernetes and Docker.
- Understands machine learning concepts such as time series forecasting and clustering.
- Follows software engineering best practices including version control and CI/CD (e.g., GitHub, GitHub Actions).
- Automates workflows using orchestration tools like Astronomer or Airflow.
- Builds and supports solutions within the Databricks platform.
- Uses machine learning frameworks and libraries such as PyTorch and scikit-learn.
*We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex (including pregnancy), national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, protected veteran status or any other protected characteristic under federal, state, or local law. We are proud to be an equal opportunity workplace.*
*We are committed to fostering an inclusive, accessible work environment that includes both providing reasonable accommodations to individuals with disabilities during the application and hiring process as well as throughout the course of one’s employment, should you need a reasonable accommodation during the application and selection process, including, but not limited to use of our website, any part of the application, interview or hiring process, please advise us so that we can provide appropriate assistance.*