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The Principal AI/Machine Learning Engineer will oversee defining and executing ZT’s roadmap for applying artificial intelligence and machine learning in manufacturing. The AI/ML Transformation Architect will be the pivotal role in shaping ZT’s future-state vision for AI & ML by identifying high-impact use cases, preparing the organization structurally and technically for adoption, and driving successful implementation of applications.
Job Responsibility:
Lead or contribute to transformation initiatives, helping set new standards for how ZT approaches manufacturing risk analysis, quality, and continuous improvement
Partner with leadership to define the vision and strategy for AI/ML adoption across manufacturing operations
Work with factory engineering, quality, and operations to identify, evaluate, and prioritize AI/ML use cases that deliver measurable business value
Collaborate across design, quality, manufacturing, test, and supplier engineering to drive solutions that integrate seamlessly into production
Define and implement new systems, processes, or frameworks that support the smart factory vision, including automation, metrology, advanced inspection, and predictive analytics
Define the organizational, data, and process changes required to prepare the business for AI/ML integration
Drive the design, development, and deployment of AI/ML solutions, ensuring successful adoption across factories
Apply AI/ML techniques to analyze manufacturing data sets – including metrology, vision inspection, event data, test results – conduct regression analysis, correlation studies, and commonality analysis
Leverage deep, data-rich environments and tools (e.g., Minitab, JMP, Python, R, SQL) to generate insights that improve yield, reliability, and throughput
Apply advanced statistical and analytical methods (regression, correlation, DOE, SPC, PFMEA, Gauge R&R, commonality studies) to identify, quantify, and control risk in complex manufacturing environments
Champion the cultural and operational transformation required for AI/ML success, including training and upskilling the industrial engineering team in new methods and approaches for mathematical computing
Serve as the bridge between industrial engineering, factory engineering teams, quality, and IT on AI/ML initiatives
Coach and nurture data stakeholders to maximize their potential and facilitate a culture of learning and growth
Demonstrate strong leadership and influence management skills, including the ability to challenge the status quo and manage key senior stakeholders
Use predictive analytics to inform PFMEA analyses that will result in actionable process controls, ensuring proactive prevention of variation rather than reactive correction
Requirements:
Advanced degree in Engineering, Computer Science, Data Science, or a related field
10–15 years of experience in high-volume, high-complexity manufacturing, with at least 5 years in leadership or transformation roles
Demonstrated expertise in statistical and analytical methods such as regression analysis, correlation analysis, DOE, SPC, PFMEA, Gauge R&R, and commonality studies
Fluency with data-driven tools such as Minitab, JMP, Python, R, SQL (or equivalent)
Track record of driving measurable improvements in yield, reliability, or process robustness
Background in electronics assembly, PCBA, servers, or other high-reliability industries
Experience with applying AI/ML toolsets to statistical problem solving, predictive analytics, or anomaly detection
Experience coaching or mentoring technical teams to upskill in statistical methods and data-driven decision-making
Strong background in leveraging manufacturing data (metrology, vision systems, event logs, quality data) to build AI/ML-enabled solutions
Proven ability to drive organizational changes in data-driven transformations
Advanced skills in mathematical computing with at least one programming language (e.g. Python, R, Java, or equivalents)
Advanced skills in data visualization / presentation skills
Excellent communication skills with the ability to engage at both executive and technical levels
Ability to convert complex (often data driven) topics to clear overviews and insights
Proven ability to perform effectively in a demanding environment with changing workloads and deadlines
Growth mindset
Takes independent initiative to complete projects with a sense of urgency
Nice to have:
MBA or exposure to business, finance or economics is advantageous
Fluency with continuous improvement / lean programs
What we offer:
Competitive base salary
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
Structured training programs and on-the-job learning opportunities
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