Principal AI/ML Engineer

About the Role

The Principal AI/Machine Learning Engineer will define and execute the AI/ML roadmap for manufacturing. This role shapes the organization’s future vision for AI and machine learning by identifying high‑value use cases, preparing teams and systems for adoption, and driving successful end‑to‑end implementation.

Duties

• Lead transformation initiatives that elevate manufacturing risk analysis, quality, and continuous improvement.
• Partner with leadership to build the AI/ML strategy for manufacturing operations.
• Identify, evaluate, and prioritize high‑impact AI/ML use cases with engineering, quality, and operations teams.
• Drive cross‑functional collaboration to integrate AI/ML solutions into production workflows.
• Define and implement systems, processes, and frameworks that support smart‑factory capabilities (automation, metrology, advanced inspection, predictive analytics).
• Establish organizational, data, and process readiness for AI/ML adoption.
• Lead the design, development, and deployment of AI/ML solutions across factory environments.
• Analyze manufacturing data (metrology, vision systems, event logs, test results) using advanced statistical and ML techniques.
• Use tools such as Minitab, JMP, Python, R, and SQL to generate insights that improve yield, reliability, and throughput.
• Apply methods such as regression, correlation, DOE, SPC, PFMEA, Gauge R&R, and commonality studies to quantify and mitigate manufacturing risk.
• Serve as the connector across industrial engineering, factory engineering, quality, and IT for AI/ML initiatives.
• Coach data stakeholders, refine ideas, and guide analysis to generate meaningful solutions.
• Use predictive analytics to inform PFMEA and develop proactive process controls.

Requirements

• Advanced degree in Engineering, Computer Science, Data Science, or related field.
• 10–15 years in high‑volume, complex manufacturing; 5+ years in leadership or transformation roles.
• Expertise in statistical methods (regression, DOE, SPC, PFMEA, Gauge R&R, correlation, commonality studies).
• Proficiency with data tools: Minitab, JMP, Python, R, SQL.
• Proven impact on yield, reliability, or process robustness.
• Background in electronics assembly, PCBA, servers, or high‑reliability industries (aerospace, medical devices, automotive, etc.).
• Experience applying AI/ML to statistical modeling, predictive analytics, or anomaly detection.
• Experience mentoring technical teams in data‑driven decision‑making.
• Strong skills in analyzing manufacturing data (metrology, vision, event logs, quality data) to build AI/ML solutions.
• Demonstrated ability to lead organizational change in data‑driven transformations.
• Expertise in mathematical computing with languages such as Python, R, or Java.
• Strong visualization and communication skills, able to distill complex topics into actionable insights.

Benefits

• Performance-based annual bonus eligibility
• 401(k) retirement savings plan
• Tuition reimbursement for eligible education programs
• Comprehensive medical, dental, and vision coverage with access to leading providers
• Mental health resources and employee wellness support programs
• Company-paid life and disability insurance
• Paid time off (PTO) and company-paid holidays
• Parental leave and family care support programs

Sound like a fit? Apply today!