Imperial Supplies, a Grainger company, is seeking a Machine Learning Engineer in Lake Forest, IL. In this role, you will be responsible for designing and implementing data pipelines, developing and deploying machine learning models, and managing the CI/CD infrastructure for machine learning systems.
What You'll Do
- Design and implement distributed data pipelines using Apache Spark and Databricks to ingest, transform, and store large volumes of structured and unstructured data.
- Develop and deploy machine learning models for low-latency, real-time inference using Amazon SageMaker and containerized services.
- Construct and manage CI/CD pipelines for machine learning infrastructure using tools like ArgoCD, Helm, and GitHub Actions to automate deployment and lifecycle management.
- Integrate and orchestrate asynchronous workflows and real-time data streams using Apache Kafka, AWS Lambda, and Step Functions to enable feature computation and scalable ML inference.
What We're Looking For
- Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, Data Science, or a related field.
- 2 years of related professional experience.
- Experience designing and implementing distributed data pipelines with Apache Spark and Databricks.
- Experience developing and deploying machine learning models for real-time inference using Amazon SageMaker and containerization.
- Experience constructing and managing CI/CD pipelines for ML infrastructure with ArgoCD, Helm, and GitHub Actions.
- Experience integrating and orchestrating workflows using Apache Kafka, AWS Lambda, and Step Functions.
Technical Stack
- Apache Spark, Databricks
- Amazon SageMaker
- ArgoCD, Helm, GitHub Actions
- Apache Kafka, AWS Lambda, AWS Step Functions
Work Mode
This position operates on a hybrid schedule and is based in Lake Forest, IL.
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.
