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崗位職責(zé)：
- Design and promote the application scheme of multimodal large models for visual quality inspection (such as defect detection, weld quality analysis), intelligent production scheduling, predictive maintenance and other scenarios in auto parts manufacturing;
針對(duì)汽車零部件制造中的視覺質(zhì)檢（如缺陷檢測(cè)、焊縫質(zhì)量分析）、智能排產(chǎn)、預(yù)測(cè)性維護(hù)等場(chǎng)景，設(shè)計(jì)并推動(dòng)多模態(tài)大模型的應(yīng)用方案；
- Actively track cutting-edge technologies such as multimodal large models, diffusion models, and reinforcement learning, and explore their innovative applications in industrial scenarios such as production process optimization;
積極跟蹤多模態(tài)大模型、擴(kuò)散模型、強(qiáng)化學(xué)習(xí)等前沿技術(shù)，探索其在生產(chǎn)流程優(yōu)化等工業(yè)場(chǎng)景的創(chuàng)新應(yīng)用；
- Build a data perception system for industrial environments, realize the collection and processing of multi-source data (such as images, sensor data, text, etc.), and generate decision-making instructions based on AI models ;
構(gòu)建面向工業(yè)環(huán)境的數(shù)據(jù)感知體系，實(shí)現(xiàn)多源數(shù)據(jù)（如圖像、傳感器數(shù)據(jù)、文本等）的采集與處理，并基于AI模型生成決策指令；
- Proficient in and applying RAG (retrieval-augmented generation) and agent task automation to integrate them into the solution;
熟練掌握并應(yīng)用RAG（檢索增強(qiáng)生成）、智能體（Agent）任務(wù)自動(dòng)化等技術(shù)，將其融入解決方案
- Refine the results of AI application projects, form standardized industry solutions and typical cases, and use them for external promotion and internal knowledge precipitation, helping to build a closed loop of AI application ecology;
提煉AI應(yīng)用項(xiàng)目成果，形成標(biāo)準(zhǔn)化的行業(yè)解決方案與典型案例，用于對(duì)外推廣和內(nèi)部知識(shí)沉淀，助力構(gòu)建AI應(yīng)用生態(tài)閉環(huán)；
- Assist in the integration, testing, validation, and deployment of AI projects with existing manufacturing systems (e.g., MES, SCADA, PLC), ensuring project timelines and quality standards are met;
協(xié)助完成AI項(xiàng)目與現(xiàn)有制造系統(tǒng)（如MES, SCADA,）的集成、測(cè)試驗(yàn)證與上線應(yīng)用，確保項(xiàng)目進(jìn)度與質(zhì)量；
- Data cleaning and data into the lake;
數(shù)據(jù)清理與數(shù)據(jù)入湖；
- AI system big data integration and post-maintenance.
AI系統(tǒng)大數(shù)據(jù)整合以及后期維護(hù)。
任職要求：
- 計(jì)算機(jī)、人工智能、機(jī)器學(xué)習(xí)、數(shù)據(jù)科學(xué)、自動(dòng)化、機(jī)械電子等相關(guān)專業(yè)本科及以上學(xué)歷；
- 三年以上AI/機(jī)器學(xué)習(xí)相關(guān)項(xiàng)目開發(fā)經(jīng)驗(yàn)，具備完整的AI項(xiàng)目落地經(jīng)驗(yàn)（從數(shù)據(jù)到部署）；有制造業(yè)（尤其是汽車、機(jī)械、電子行業(yè)）AI項(xiàng)目經(jīng)驗(yàn)者優(yōu)先；
- 熟練掌握英文的讀寫聽說(shuō)，口語(yǔ)好；
- 熟悉計(jì)算機(jī)信息系統(tǒng)架構(gòu)，熟練掌握VB、VB.NET、C++、C#、Python、Java（必須）等兩種以上開發(fā)技術(shù)，熟悉主流開發(fā)工具；接口開發(fā)；
- 熟練使用TensorFlow等深度學(xué)習(xí)框架；具備容器化（Docker/K8s） 和高性能服務(wù)開發(fā)經(jīng)驗(yàn)；
- 熟練使用OpenCV或HalCon；
- 精通機(jī)器學(xué)習(xí)/深度學(xué)習(xí)框架（如PyTorch, TensorFlow），有時(shí)間序列分析（預(yù)測(cè)性維護(hù)）和計(jì)算機(jī)視覺（缺陷檢測(cè)）項(xiàng)目經(jīng)驗(yàn)；
- 掌握異常檢測(cè)算法（如自編碼器、隔離森林）和根因分析方法；
- 了解工業(yè)自動(dòng)化系統(tǒng)（如PLC、SCADA）和常見工業(yè)通信協(xié)議（如OPC UA, MQTT, Modbus, Profinet）者優(yōu)先。