Work Location Type: Hybrid 

 

As a leading industrial distributor with operations primarily in North America, Japan and the United Kingdom, We Keep The World Working® by serving more than 4.5 million customers worldwide with products delivered through innovative technology and deep customer relationships. With 2023 sales of $16.5 billion, we’re dedicated to providing value for customers, fostering an engaging culture for team members and driving strong financial results.

 

Our welcoming workplace enables you to learn, grow and make a difference by keeping businesses running and their people safe. As a 2024 Glassdoor Best Place to Work and a Great Place to Work-Certified™ company, we’re looking for passionate people to join our team as we continue leading the industry over our next 100 years.

 

 

Position Details: 

Grainger's inventory planning team manages over 10 million SKU's and nearly $2 billion in inventory across 500 DC's and branches in North America. We’re hiring a Machine Learning Engineer II, Inventory Optimization and Advanced Analytics to support and develop solutions to support a team of data scientist to make analytics-based decisions on where, when, and how much inventory is needed to satisfy customers’ needs. You will report to the Manager, Machine Learning Engineer, Inventory Optimization & Advanced Analytics. This role reports to the Mgr, Machine Learning Engineer and can be based in Lake Forest or Chicago, IL on a hybrid basis. Full-time remote candidates are also encouraged to apply. Some travel will be required for team meetings at our corporate offices.

  

You Will: 

Create scalable, efficient, automated processes for large-scale data analyses, model development, model validation and deployment 

Oversee machine learning solutions, collaborating with data scientists to foster ongoing continuous improvement  

Explore emerging technologies to evaluate their potential application to our team's objectives, and responsible for the deployment of innovative solutions that align with our strategic goals 

Automate critical system operations, design robust ETL pipelines, and develop web applications that enable stakeholders to effectively interact with and utilize our ML and ERP systems 

 

You Have: 

2+ years of experience deploying and maintaining production machine learning solutions with Python 

Exposure or familiarity with AWS products (s3, ECR, Secrets Manager) 

Follow software engineering practices and use version control and CI/CD tools (GitHub, GitHub Actions) 

Proficient in usage of databases (Snowflake, DuckDB) and querying languages (e.g. SQL) 

Experience working in containerization ecosystems (Kubernetes, Docker) 

Familiarity with machine learning models and concepts (time series forecasting, clustering)  

Experience automating workflows using orchestration (Astronomer, Airflow) 
 

Our Benefits:
With benefits starting day one, Grainger is committed to your safety, health, and wellbeing. Our programs provide alternatives to meet our team members' individual needs. Check out some of the rewards available to you at Grainger:
Medical, dental, vision, and life insurance plans
Paid time off (PTO) and 6 company holidays per year
Automatic 6% 401(k) company contribution each pay period
Employee discounts, parental leave, 3:1 match on donations and tuition reimbursement
A comprehensive set of emotional, financial, physical, and social wellbeing programs

 

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We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace.

 

We are committed to fostering an inclusive, accessible 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.  With this in mind, should you need a reasonable accommodation during the application and selection process, please advise us so that we can provide appropriate assistance.