Senior ML Engineer: Production ML Pipelines (Hybrid)

Zoro Tools; Chicago (IL); Hybrid; USD 134,000 - 224,000; Full time

Benefits offered by this job

Medical, dental, vision, and life保险

PTO + holidays

401(k) company match

Employee discounts

Tuition reimbursement

Student loan refinancing

Financial counseling

Maternity & parental leave

Job summary

Grainger is seeking a Senior Machine Learning Engineer - GUS to design and deliver scalable, production-grade ML solutions. You will lead data pipelines, deploy ML and operations research models, and build tools to empower data scientists and stakeholders.

Responsibilities include maintaining ETL pipelines, mentoring teammates, and integrating new technologies to support business goals. The role requires 3+ years of production ML experience and a strong foundation in Python, AWS, and modern data

Qualifications

• Bachelor's Degree in Computer Science, Engineering, or a related field.
• Master's Degree in related technical field or equivalent practical experience preferred.
• 3+ years Production ML, optimization, modern data tools, and scalable engineering practices required.
• 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.

Responsibilities

• 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.

Skills

Production ML

Python

SQL

CI/CD

AWS

Education

Bachelor's Degree in Computer Science or Engineering

Master's Degree in related field

Tools

Docker

Kubernetes

Snowflake

DuckDB

Databricks

PyTorch

scikit-learn

GitHub Actions

Job description

Grainger is seeking a Senior Machine Learning Engineer - GUS to design and deliver scalable, production-grade ML solutions. You will lead data pipelines, deploy ML and operations research models, and build tools to empower data scientists and stakeholders.

Responsibilities include maintaining ETL pipelines, mentoring teammates, and integrating new technologies to support business goals. The role requires 3+ years of production ML experience and a strong foundation in Python, AWS, and modern data