Senior AI Manufacturing Engineer - Process Optimization

Howmet Aerospace; Whitehall Township (MI); On-site; USD 110,000 - 160,000; Full time

Job summary

Howmet Aerospace in Whitehall, MI is seeking a Process Engineer to design, document, and optimize manufacturing processes by integrating AI analytics to boost efficiency, cut waste, and shorten cycle times on the factory floor.

You will collaborate with the AI deployment team to ensure clean data, pilot AI-driven changes, and ensure safety, quality, and regulatory compliance while delivering measurable ROI.

Qualifications

• BS in Industrial/Mechanical/Chemical Engineering from an accredited institution.
• 5+ years manufacturing experience.
• Up to 50% travel.

Responsibilities

• Design, document, and optimize manufacturing processes, incorporating AI analytics for efficiency gains, waste reduction, and cycle-time improvements.
• Analyze real-time production data (from sensors/IoT) to identify bottlenecks and recommend AI model-driven changes.
• Provide manufacturing domain knowledge as it relates to process engineering (materials, processes, KIV-KOV relationships), to guide AI model development, feature selection, and validation of AI recommendations.
• Collaborate with AI engineers to ensure processes generate clean, labeled data for training models; implement AI recommendations on the factory floor.
• Lead pilot projects for AI-based process control and agentic problem solving (e.g., waste / scrap reduction) and validate ROI.
• Ensure compliance with safety, quality, and regulatory standards while introducing AI tools.

Skills

Manufacturing experience

Six Sigma

Lean

Education

BS in Industrial/Mechanical/Chemical Engineering

Tools

Python

Tableau

Job description

Howmet Aerospace in Whitehall, MI is seeking a Process Engineer to design, document, and optimize manufacturing processes by integrating AI analytics to boost efficiency, cut waste, and shorten cycle times on the factory floor.

You will collaborate with the AI deployment team to ensure clean data, pilot AI-driven changes, and ensure safety, quality, and regulatory compliance while delivering measurable ROI.