Principal AI / Machine Learning Engineer

ZT Group Intl, Inc. dba ZT Systems; Secaucus (NJ); On-site; USD 141,000 - 188,000; Full time

Benefits offered by this job

Competitive base salary

Performance-based annual bonus eligibility

401(k) retirement savings plan

Tuition reimbursement

Comprehensive medical, dental, and vision coverage

Job summary

ZT Group Intl, Inc. dba ZT Systems is looking for a Principal AI/Machine Learning Engineer to lead the integration of AI/ML solutions in manufacturing. You will define a strategic roadmap, partner with leadership, and drive the implementation of AI tools to enhance productivity.

This role requires an advanced degree and significant experience in high-complexity environments. A competitive salary and benefits package, including bonuses and a comprehensive health plan, are offered.

Qualifications

• 10–15 years of experience in high-volume, high-complexity manufacturing.
• Expertise in statistical and analytical methods.
• Fluency with tools like Python, R, SQL to analyze large datasets.

Responsibilities

• Define and execute AI/ML roadmap for manufacturing.
• Lead transformation initiatives for manufacturing processes.
• Drive design, development, and deployment of AI/ML solutions.

Skills

Statistical and analytical methods

Data-driven tools

Leadership

Coaching and mentoring

Education

Advanced degree in Engineering, Computer Science, Data Science, or related field

Tools

Python

R

SQL

Minitab

JMP

Job description

About the Role

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 shape 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.

What You Will Do

• 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 – conducting 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.
• Act as a thought partner and subject‑matter expert to refine ideas, generate hypotheses, and analyze data to formulate solutions.
• 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.

What You Bring

• 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 (not necessarily people management).
• 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) to analyze and interpret large, complex datasets.
• Track record of driving measurable improvements in yield, reliability, or process robustness.
• Background in electronics assembly, PCBA, servers, or other high‑reliability industries (e.g., aerospace, medical devices, automotive).
• Experience 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), and the ability to learn technical methods and tools independently.
• Advanced skills in data visualization / presentation, including simplifying results and statistical concepts into actionable insights.
• Excellent communication skills with the ability to engage at both executive and technical levels.
• Ability to convert complex subjects to clear overviews and insights.
• Proven ability to perform effectively in a demanding environment with changing workloads and deadlines.
• Growth mindset with independent initiative and a sense of urgency.
• Nice to have: MBA or exposure to business, finance or economics; fluency with continuous improvement / lean programs.

Salary and Compensation

The typical base salary for this position is expected to be between $141,000 and $188,000 annually. The final base salary will be determined on an individual basis, taking into account experience, skills, knowledge, education and/or certifications. Base salary is just one component of ZT Systems’ total rewards philosophy, which also includes bonus, paid time off, generous 401(k) match, tuition reimbursement, wellbeing resources, and more.

Benefits

• 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
• 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
• Matching gifts and volunteer programs to support causes you care about

Equal Opportunity Employer

ZT Group Int’l. is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind. ZT Systems provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Certain positions may require the applicant to be a U.S. citizen or national, a U.S. lawful permanent resident, a refugee, or an asylee, or to be eligible to obtain an export control license or license exception from the Bureau of Industry and Science & U.S. Department of Commerce. All offers of employment will be conditional on meeting these requirements.