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Senior Machine Learning Operations Engineer

PPG

Salary not specified
Aug 25, 2025
Pittsburgh, PA, US
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PPG Industries, Inc. is seeking a Senior Machine Learning Operations Engineer to deploy, manage, and optimize machine learning models for the development of proprietary paint coatings products, ensuring seamless integration and operation of these solutions.

Requirements

  • AI data models/simulation tools for coatings products and batch color correction projects
  • data models for predicting color as a function of formula composition for coating technologies
  • using artificial intelligence and machine learning algorithms to improve product quality, output, and cost related to manufacturing processes
  • machine learning algorithms developed for paint coatings formulations

Responsibilities

  • driving the scalability, reliability, and performance of machine learning systems for paint coatings formulations
  • designing, implementing, and maintaining scalable machine learning infrastructure and pipelines
  • deploying and monitoring machine learning models in production environments
  • optimizing model performance and ensuring reproducibility
  • developing and maintaining CI/CD pipelines for machine learning workflows
  • implementing best practices for model versioning, testing, and validation
  • troubleshooting and resolving issues related to model deployment and performance

Other

  • work-at-home Senior Machine Learning Operations Engineer position (with the ability to telecommute with appropriate telecommuting systems; the remote worksite must be within commuting distance of Pittsburgh, PA for weekly trips to the corporate office)
  • master’s degree (or foreign equivalent) in Data Science, Computer Science, Finance, Mathematics, Statistics, or a related field plus two (2) years of experience in a related position
  • mentoring and providing guidance to junior team members
  • ensuring the security and compliance of machine learning systems
  • commitment and drive to strive today to do better than yesterday – everyday