Senior ML Engineer - MLOps, Cloud & Production

Sherwin-Williams; Cleveland (OH); On-site; USD 140,000 - 210,000; Full time

Job summary

Sherwin-Williams is seeking a Senior Machine Learning Engineer to design, develop, test, and operationalize ML and data solutions across cloud environments. You will collaborate with business analysts, data scientists, software and platform engineers, QA, and project managers to deliver high-quality ML systems with robust CI/CD, testing, and monitoring.

The role emphasizes MLOps, cloud-based tooling, scalable microservices, and strong communication skills to translate business needs into

Qualifications

• Bachelor's degree in Computer Science or Computer Engineering; 7+ years of software development experience if no degree.
• 4+ years of experience in ML, MLOps, and/or software development.
• Knowledge of SDLC, MLOps, and DevOps practices.
• Experience with cloud platforms, databases, and SQL.
• Ability to develop, integrate, test and deploy software for cloud-based tools.
• Excellent written and verbal communication skills.
• Experience in developing microservices and various integration patterns.

Responsibilities

• Design, develop, and deploy ML models and data solutions aligned with business requirements.
• Train, validate, and optimize models for performance and accuracy.
• Write high-quality, scalable code and maintain technical documentation.
• Develop and maintain CI/CD pipelines; drive automated testing and monitoring.
• Collaborate across analytics, software, and IT to translate requirements into production solutions.
• Provide incident response, root-cause analysis, and resiliency testing.
• Stay current with ML and MLOps advancements and implement innovative solutions.

Skills

ML & MLOps

CI/CD pipelines

Cloud platforms

DevOps

Microservices

SQL

Communication

Education

Bachelor's Degree in Computer Science or Computer Engineering

Tools

Databricks

Docker

Kubernetes

Git

Job description

Sherwin-Williams is seeking a Senior Machine Learning Engineer to design, develop, test, and operationalize ML and data solutions across cloud environments. You will collaborate with business analysts, data scientists, software and platform engineers, QA, and project managers to deliver high-quality ML systems with robust CI/CD, testing, and monitoring.

The role emphasizes MLOps, cloud-based tooling, scalable microservices, and strong communication skills to translate business needs into