AI Manufacturing Engineer

Location: United States of America, California, Santa Ana.Position SummaryThe AI Engineer is a hands‑on, shop‑floor engineer who applies AI and data‑enabled tools to improve safety, quality, throughput, productivity, and time-to‑proficiency in skilled labor roles. This role partners directly with Operations, Quality, Maintenance, EHS, Supply Chain, and Training to translate real manufacturing problems into practical, scalable AI applications that are adopted and sustained on the floor.The role is a Manufacturing Engineer/AI Engineer hybrid, spending approximately 50‑60% of the time developing and maintaining plant AI applications and 40‑50% in manufacturing, working alongside operators, supervisors, and maintenance teams to ensure solutions reflect real process behavior and are embedded into standard work.Key ResponsibilitiesPlant AI Enablement & Manufacturing PartnershipPartner with Operations, Quality, Maintenance, EHS, Supply Chain, and Training to identify and prioritize high‑value AI use cases tied to safety, quality, throughput, productivity, and workforce capability.Build and manage a plant AI opportunity pipeline, including use cases, value hypotheses, owners, required data, timing, and success metrics.Define clear problem statements, requirements, and KPIs (e.g., defect escape reduction, downtime reduction, cycle‑time improvement, injury risk reduction, faster time to proficiency).Lead pilots from concept through shop‑floor adoption, including data readiness, trial design, operator input, training, launch, and sustainment.Ensure AI solutions are simple, explainable, and usable for operators and supervisors, integrated into standard work and leader routines.Identify and mitigate operational and safety risks (failure modes, false positives/negatives, bias, safety impacts) and ensure controls and escalation paths are in place.Manufacturing & Process EngineeringImprove manufacturing processes across machining, forming, assembly, and inspection operations.Lead root‑cause analysis related to scrap, rework, downtime, delinquencies, training‑related errors, and safety risks.Develop, improve, and sustain standard work, process flows, layouts, tooling, and capability studies.Support equipment commissioning, process optimization, and reliability improvement in partnership with Maintenance and Operations.AI Application Development (Plant‑IT Collaboration)Own hands‑on development, deployment, and sustainment of lightweight AI‑enabled plant applications (prototypes through targeted production features) using Division and Corporate IT/AI standards for architecture, security, and governance.Serve as the manufacturing product owner for plant AI applications by defining requirements, validating outputs against shop‑floor reality, and ensuring usability for end users.Lead the end‑to‑end lifecycle for plant AI solutions (design, development, testing, release, training, sustainment) and elevate design decisions and risks as needed.Develop and maintain solutions such as Databricks Apps, internal dashboards, decision tools, and AI‑assisted workflows that operationalize manufacturing use cases.Integrate APIs, model endpoints, and data services into user‑facing tools; document assumptions, controls, and escalation paths.Use Git and follow agreed release, testing, and change‑management practices; provide Tier 1 support and coordinate enhancements with IT and Corporate AI teams.Workforce Capability & Time to Proficiency ImprovementApply AI‑enabled training and development tools to reduce time to proficiency in key skilled labor roles (e.g., machinists, thread‑roll operators, maintenance technicians, inspectors).Partner with Engineering, Operations, and Training to identify skill gaps, high‑error steps, and learning friction points.Develop AI‑supported tools such as digital work instructions, visual job aids, troubleshooting assistants, and skill‑progression checkpoints.Enable supervisors and trainers with data‑driven insights to focus coaching, standardize training across shifts, and reinforce correct behaviors.Validate training effectiveness through faster readiness for independent work, reduced early‑stage defects and downtime, and improved retention.Data, Continuous Improvement & Change LeadershipUse MES, SPC, quality systems, downtime tracking, sensor/PLC data, and learning data to drive improvement.Validate AI outputs through hands‑on observation and process confirmation.Establish KPIs, control plans, and visual management to sustain gains.Act as a change agent by training and coaching operators and supervisors and embedding improvements into standard work and leader routines.Reporting & GovernancePrimary accountability is to plant leadership for operational results and performance improvement.Dotted‑line alignment with Division IT to ensure consistency with enterprise AI strategy, security, and standards.Prepare and deliver quarterly updates to cross‑functional leadership (Division, Corporate AI, IT, Quality, Operations, HR, and Site Leadership).Qualifications & SkillsEducation / ExperienceBachelor's degree in Manufacturing Engineering, Mechanical Engineering, Computer Science, or related field; experience in a high‑mix/high‑volume manufacturing environment strongly preferred.Technical & FunctionalStrong manufacturing engineering fundamentals (process capability, variation reduction, PFMEA/control plans, standard work).Proven structured problem solving (5‑Why, fishbone, DOE where appropriate) and Lean/CI leadership.Applied AI and digital fluency with light coding capability; able to build prototypes and small production applications.Proficiency with Python or similar scripting; familiarity with simple UIs (Streamlit/Dashstyle) and REST APIs.Working knowledge of MES, SPC, quality systems, downtime systems, and industrial data sources.Familiarity with Git and basic software delivery practices.Leadership & CommunicationStrong cross‑functional partnering skills; influences without authority.Effective communicator with hourly teams and leaders.Demonstrated change‑management capability and safety mindset.What Success Looks LikeSustained reductions in scrap, rework, downtime, and training‑related errors.Faster time to proficiency in skilled labor roles.AI applications that are used daily and embedded in standard work.Measurable improvements in safety, quality, delivery, and cost.Manufacturing teams that trust and rely on data‑driven insights.All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.Compensation & BenefitsPay range: $80,000 to $120,000 USD. Salary is based on a variety of factors. Eligible to participate in the Company's Quarterly Cash Bonus Plan and receive 120 hours paid time off and 10 paid holidays per year. Benefits include medical, dental, vision, basic life insurance, and a 401(k) plan.Export ControlsThis position requires use of information or access to production processes subject to national security controls under U.S. export control laws and regulations (including, but not limited to the International Traffic in Arms Regulations (ITAR) and the Export Administration Regulations (EAR)). To comply with those regulations, this position may require applicants to be U.S. Persons (i.e., U.S. citizens, U.S. lawful permanent residents, protected individuals as defined by 8 U.S.C. 1324b(a)(3)), or eligible to obtain the required export authorizations from the U.S. Department of State or the U.S. Department of Commerce.#J-18808-Ljbffr