Machine Learning Engineer - 328057

Grainger Businesses • Lake Forest, IL

1d • Hybrid

About The Position

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 maintenances, repair and operating (MRO) products and services, including technical support and inventory management. In the Endless Assortment segment, Zoro.com offers customers access to more than 14 million products, and MonotaRO.com offers more than 24 million products. For more information, visit www.grainger.com. 

Grainger Management LLC is seeking a Machine Learning Engineer in Lake Forest, IL with the following requirements: Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, Data Science, or related field plus 2 years of related experience. Prior experience must include: Design and implement distributed data pipelines using Apache Spark and Databricks to ingest, transform, and store large volumes of structured and unstructured data across multi-stage environments; Develop and deploy machine learning models for low-latency, real-time inference using Amazon SageMaker and containerized services, including the implementation of bring-your-own-container (BYOC) strategies and endpoint optimization; Construct and manage CI/CD pipelines for machine learning infrastructure using tools such as ArgoCD, Helm, and GitHub Actions to automate model deployment, rollback, and lifecycle reproducibility across staging and production environments; Integrate and orchestrate asynchronous workflows and real-time data streams using Apache Kafka, AWS Lambda, and Step Functions to enable feature computation, message-driven processing, and scalable ML inference pipelines. Up to 60% remote work allowed.

Compensation: The anticipated base pay range for this position is $110,500 to $184,100 which reflects the potential base pay at the time of this posting. Base pay will depend on factors such as work location, relevant experience, and skills. Grainger reserves the right to amend, modify, or terminate compensation and benefit programs in its sole discretion at any time, consistent with applicable law.

Rewards and Benefits: To learn about Grainger’s benefits, please visit: https://experience100.ehr.com/grainger/Home/Tools-Resources/Key-Resources/New-Hire

Please submit resume to https://jobs.grainger.com, reference job # 328057.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, Data Science, or related field plus 2 years of related experience.
• Design and implement distributed data pipelines using Apache Spark and Databricks to ingest, transform, and store large volumes of structured and unstructured data across multi-stage environments
• Develop and deploy machine learning models for low-latency, real-time inference using Amazon SageMaker and containerized services, including the implementation of bring-your-own-container (BYOC) strategies and endpoint optimization
• Construct and manage CI/CD pipelines for machine learning infrastructure using tools such as ArgoCD, Helm, and GitHub Actions to automate model deployment, rollback, and lifecycle reproducibility across staging and production environments
• Integrate and orchestrate asynchronous workflows and real-time data streams using Apache Kafka, AWS Lambda, and Step Functions to enable feature computation, message-driven processing, and scalable ML inference pipelines

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level