Position Purpose
This Industry AI & Smart manufacturing Engineer leads the full-cycle identification of AI-powered intelligent solutions across regional manufacturing sites. You will dissect end-to-end shopfloproduction workflows, mine high-value application scenarios, leverage AI, computer vision predictive analytics to drive intelligent process optimization, unmanned automation data-based operational decision-making, accelerating the factory-wide digital transformation roadmap.
Role & responsibilities
1. Walk down production lines to audit manual operations, equipment performance process bottlenecks, identify high-potential AI automation & optimization scenarios with clear ROI projections.
2. Independently design, develop iterate industrial AI solutions covering visual quality inspection, equipment predictive maintenance, process parameter self-optimization intelligent workflow automation.
3. Cooperate closely with internal IT data teams to unify shopflodata collection standards, clean, label structure multi-source industrial datasets fmodel training.
4. Complete technical feasibility assessment, cost-benefit calculation risk evaluation fall proposed AI use cases, output formal business validation reports.
5. Lead end-to-end AI pilot projects: solution design, offline model training, on-site deployment, trial run verification performance tuning. Scale verified high-value solutions to full production lines multi-site factories.
6. Realize seamless data & logic interconnection between AI intelligent modules existing factory core systems (MES, ERP, automation control platforms).
7. Establish long-term model monitoring mechanisms, continuously retrain optimize AI models to adapt to changing production materials, product specs process conditions.
8. Deliver standardized operation training SOP documents fproduction engineering teams to independently operate maintain AI intelligent tools.
9. Strictly implement factory EHS management rules, industrial data security specifications global corporate manufacturing standards throughout all AI project phases.
Knowledge & Skills
Solid foundational understanding of AI/ML algorithms mature industrial AI landing scenarios (defect inspection, predictive maintenance, process parameter optimization, etc.).
Proficient in data development tools: Python data processing stack, SQL database query & data warehouse extraction.
Hands-on implementation experience with mainstream industrial AI modules: computer vision inspection, process mining, equipment predictive analytics, intelligent scheduling.
Comprehensive shopflomanufacturing knowledge, familiar with mass production assembly workflows on-site operation logic.
Basic grasp of industrial automation infrastructure core data sources: PLC, SCADA, MES, production sensors, equipment edge terminals.
Mature experience in workflow diagnosis, bottleneck analysis data-backed process optimization.
Excellent bilingual communication capability: able to translate complex algorithmic logic plain operational guidance ffrontline production teams; fluent written & verbal English fcross-regional global alignment.
Required Experience & Qualifications
Education Background: Bachelor’s degree above in Data Science, Artificial Intelligence, Automation, Mechatronics, Computer Science, Industrial Engineering other related engineering majors.
Core Working Experience: 3–8 years relevant professional experience in industrial AI, manufacturing data analytics smart manufacturing engineering.
Mandatory Experience: Proven track record of landing AI/ML solutions in actual mass-production factory environments; hands-on project delivery experience preferred.
Industry Knowledge: Systematic understanding of industrial engineering theories shopfloprocess optimization methodologies.
Core Capability Requirement: Strong logical analysis, independent project planning end-to-end execution capability.
Preferred Background: Working experience in multinational manufacturing enterprises with digital transformation projects is a majplus.
Strong analytical project execution capability
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