Remote Lead ML Engineer & MLOps Architect

Sherwin-Williams; Cleveland (OH); À distance; USD 140 000 - 190 000; Plein temps

Résumé du poste

Sherwin-Williams is seeking a Lead Machine Learning Engineer to design, develop, test, and operationalize ML and data solutions across cloud-based environments. You will guide model training, validation, and optimization, and ensure scalable, well-documented code with strong SDLC practices.

You will lead MLOps implementations, automate testing, and monitor deployments while collaborating with data scientists, software and platform engineers, QA, and PMs.

Qualifications

• Bachelor's Degree in Computer Science or Computer Engineering or equivalent with 9+ years of software development experience.
• 6+ years of experience in ML, MLOps, and/or software development.
• Proficient in SDLC, MLOps, and DevOps practices and tools.
• Experience with cloud platforms and software deployment for cloud-based tools.
• Strong SQL and relational database knowledge.
• Excellent written and verbal communication skills.
• Experience building microservices and integration patterns.
• Familiarity with Generative AI tools in SDLC (e.g., Claude Code, Codex, GitHub Copilot).
• Experience with Generative AI systems (LLMs, RAG, agent workflows).
• Knowledge of data science/statistics relevant to ML.

Responsabilités

• Design, develop, test, and operationalize ML and data solutions.
• Oversee design, development, and deployment of ML models per requirements.
• Guide training, validation, and optimization of models for performance.
• Provide strategic direction for maintainable, scalable code.
• Maintain technical documentation including deployment workflows and procedures.
• Lead MLOps efforts: CI/CD pipelines, testing, and monitoring.
• Foster cross-functional collaboration to translate business needs into production solutions.
• Provide ongoing support including incident management and observability.
• Stay updated on ML and MLOps advancements and introduce innovations.

Connaissances

ML/MLOps

SDLC methodologies

Cloud platforms

Programming: Python/R

Communication

Formation

Bachelor's Degree in CS/CE

Outils

Docker

Kubernetes

Jenkins

MLflow

GitHub

Description du poste

Sherwin-Williams is seeking a Lead Machine Learning Engineer to design, develop, test, and operationalize ML and data solutions across cloud-based environments. You will guide model training, validation, and optimization, and ensure scalable, well-documented code with strong SDLC practices.

You will lead MLOps implementations, automate testing, and monitor deployments while collaborating with data scientists, software and platform engineers, QA, and PMs.