Director- AI Engineering at Eaton USA

Raleigh, North Carolina, United States -

Full Time

Start Date

Immediate

Expiry Date

26 Jan, 26

Salary

0.0

Posted On

28 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Engineering, Data Science, Digital Transformation, Predictive Maintenance, Defect Detection, Process Optimization, Supply Chain Analytics, MLOps, Python, SQL, PyTorch, TensorFlow, OSIsoft PI, Snowflake, Kubeflow, CI/CD Pipelines, Generative AI

Industry

electrical;Appliances;and Electronics Manufacturing

Description

Responsibilities include researching emerging AI technologies, assessing their business implications, and advising on strategic investments. Build and lead a high-performing AI engineering team focused on scalable, production-grade solutions for industrial environments. Establish enterprise-wide AI governance, including ethical use, compliance with industrial standards, and risk mitigation. Develop policies and frameworks for responsible AI, model transparency, and bias mitigation in safety-critical environments. Evaluate emerging AI technologies and vendor partnerships to inform build-vs-buy decisions for manufacturing applications. Partner with operations, engineering, and supply chain leaders to identify high-impact AI opportunities across production, logistics, and maintenance. Lead the adoption of generative AI, computer vision, predictive maintenance, and intelligent automation to optimize manufacturing processes. Bachelor's degree in Engineering and/or Computer Science from an accredited instituition. Minimum 10 years of experience in engineering or technology leadership, with a focus on AI, data science, or digital transformation. Minimum 2 years of enterprise IT leadership experience defining and executing AI strategies for a multi-billion-dollar industrial organization. Must be authorized to work in the U.S. without company sponsorship. Proven success delivering AI-powered solutions at scale in manufacturing or industrial environments. Experience with AI applications such as predictive maintenance, defect detection, process optimization, and supply chain analytics. Deep understanding of AI/ML frameworks (e.g., PyTorch, TensorFlow), industrial data platforms (e.g., OSIsoft PI, Snowflake), and programming languages (Python, SQL). Familiarity with MLOps tools and practices (e.g., MLflow, Kubeflow, CI/CD pipelines) and edge deployment strategies. Strong track record of influencing senior stakeholders and driving enterprise-wide transformation in manufacturing settings.

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Responsibilities

The Director of AI Engineering will research emerging AI technologies and lead a high-performing AI engineering team to develop scalable solutions for industrial environments. They will establish AI governance and partner with various leaders to identify high-impact AI opportunities across manufacturing processes.