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【櫃台訪客接待 50%】 -登記進出入訪客，並引導至會議室及提供茶水【行政庶務 20%】 -協助普渡、開工拜拜儀式 -小額零用金管理、簡易採購、聯絡廠商 -單據及文件登打、歸檔 -郵局寄信往返、收發分類國內外信件/包裹【總機 10%】 -接聽、過濾、轉接來電，並提供資訊及留言服務【維護辦公室環境及設備 10%】 -維持環境整齊、盆栽澆水 -補給零食區的餅乾、飲料【其他主管交辦事項 10%】【其他補充】1.保證第13薪及其他獎金2.閒暇之餘可閱讀3.可準時上下班

【工作內容】 職務性質：全職 需求人數：1~2人 職類：門市／專櫃人員 夥伴招募需求： 負責介紹及銷售門市商品提供顧客接待與需求服務（如：電話諮詢、調貨、修改、包裝及退換貨處理）負責商品進貨入庫、銷售管理及庫存管理負責商品包裝、陳列及促銷品換檔工作維持店櫃週遭之整潔具服務業及餐飲業經驗服務顧客 - 產品知識與專業建議、店務作業顧客體驗管理 - 銷售與達標、團隊合作與成長 到職滿1個月，發放$1,500獎金到職滿3個月，發放$2,000獎金到職滿6個月且通過試用期考核，發放$3,000獎金達成上述條件且到職滿12個月，另發放$6,000獎金''此為一次性獎金於到職期滿後申請給予'' 工作待遇：月薪35,500元 ~ 38,000元 上班地點：台北市松山區三民路152號 管理責任：不需負擔管理責任 出差外派：無需出差外派 上班時段：輪班制 (日班、晚班、假日班；門市營業時間：11:00~21:00) 休假制度：輪休制 (每四周 8 天例假日及休息日；國定假日另計) 可上班日：不限 歡迎身分：應屆畢業生、原住民、二度就業、中高齡 【工作條件】 工作經驗：不拘 學歷要求：不拘 科系要求：不拘 語文條件：台語 (中等)、英文 (略懂) 擅長工具：Word、PowerPoint、Excel、Outlook

1.維護與經營現有國外市場代理商，維持穩定合作關係。 2.積極開發潛在客戶與拓展市場，評估市場趨勢，制定對應的銷售策略，以達成年度業績目標。 3.配合年度業務規劃需求安排國外出差，進行洽談業務與售後服務。 4.負責訂單處理、帳款催收與客戶問題處理等日常營運作業，確保穩定順暢。 5.執行專案及主管交辦事項。*工作待遇將依經驗及能力核定*

Please apply via the JKOPAY website; we will primarily review resumes submitted through this platform.As an SDET at JKOpay, you will collaborate with RD and PM teams to conduct test development in your area of responsibility according to the project's progress. In addition to project tasks, you will assist with app-related release matters. Lastly, you will work together to maintain technical projects specific to SDET and optimize existing frameworks and processes.We expect you to possess strong communication skills, teamwork abilities, problem-solving capabilities, resilience under pressure, adaptability, proactivity, and technical expertise. Additionally, you should have a passion for and a solid understanding of the electronic payment market, and be willing to fully dedicate yourself to the product. ▶ Programming is required. • Overall quality on both the back-end side and the front-end side with the creation of test plans, cases, and reports. • Create and maintain reliable automation scripts• Ensure quality of App release by understanding new features/functions and verifying various fixes.• Review requirements/design documents and propose recommendations.• Implemented a testing tool to accelerate the testing cycle.

關於這個職位 資安研究的價值取決於執行速度。我們是一個資安研究團隊，專注開發協助企業在漏洞被利用前找出並修復問題的工具。 我們正在招募一位 AI 與工作流程自動化工程師，負責透過自動化與 AI 工具提升我們的研究與開發效率。你不需要具備資安背景，但你所建立的工具與流程將直接影響研究成果的交付速度。對於有興趣的人，你也將能夠直接接觸我們的研究團隊與他們的工作內容，如果你想往資安方向發展，這裡是一個能夠打好基礎的環境。 基本要求 具備紮實的程式基礎，並有 C/C++ 以及 Python 的實際操作經驗有實際建立自動化流程並將 AI 工具整合進真實工作流程的經驗能夠從釐清範疇到完成交付全程獨立負責 加分條件 有使用 Go 與 React 的經驗熟悉 LLM 並知道怎麼實際應用熟悉資安概念或企業 IT 環境 我們歡迎不同職涯階段的應徵者。如果你符合基本要求並有動力持續成長，歡迎投遞履歷。 【工作經驗】有 AI/自動化流程的project或實習經驗以上即可 【語言能力】不拘 【證照資格】AI相關證照 Cybersecurity research is only as effective as the speed at which it can be done. We are a security research team building tools that help organizations find and fix real vulnerabilities before they get exploited. We are looking for an AI Workflow Automation Engineer to help us move faster and more reliably. You will not be doing the security research yourself, but the automation and tooling you build will directly determine how quickly our research reaches the people who need it. For those interested, you will also have direct access to our research team and their work, making this a strong environment to build foundational knowledge in cybersecurity if that is a direction you want to grow into. Requirements Solid programming foundation with hands-on experience in C/C++ and PythonPractical experience building automation pipelines and integrating AI tools into real workflowsAble to work independently from scoping through to delivery Good to Have Experience with Go and ReactFamiliarity with LLMs and how to apply them practicallyFamiliarity with cybersecurity concepts or enterprise IT environments We welcome candidates at different stages of their careers. If you meet the requirements and are motivated to grow, we encourage you to apply.

Please apply via the JKOPAY website; we will primarily review resumes submitted through this platform.【About the Role】 Build and operate JKOPay's AI Foundation Platform and customer-facing AI features. You'll own the end-to-end delivery of LLM applications, agent workflows, and RAG systems — designing for both internal product teams and end users, in a PCI DSS-compliant financial services environment. 【Why This Role】 You'll work on AI infrastructure that ~70 engineers depend on daily, and product features that reach millions of JKOPay users — with real ownership, modern tooling, and the technical freedom to make AI work in a regulated environment. 【What You'll Do】 Ship LLM applications: prompt engineering, RAG pipelines, function calling, and multi-agent orchestration powering real product featuresOperate the AI platform: extend our LiteLLM Gateway + Langfuse + pgvector stack on GKE; build evals, observability, and CI/CD for prompts and modelsOwn AI safety governance: design data boundaries within PCI DSS scope, implement guardrails (PII detection, prompt injection defense), and support compliance auditsChoose the right model for the job: balance self-hosted vs. API, cost vs. latency, quality vs. throughputPartner across teams: work with Product, Backend, Data, and InfoSec to embed AI into the product and internal workflows

About the Role We are looking for a UI/UX Full Stack Engineer with a passion for creating powerful, intuitive, and data-rich enterprise applications tailored for the process industries—including energy, manufacturing, and industrial automation. In collaboration with data scientists, product managers, and domain experts, you will design and build the next generation of intelligent user experiences that enable complex data exploration, graph-based interaction, and persona-aware workflows. Inspired by platforms from C3.ai, Aveva, AspenTech, Palantir, and Siemens, your work will bring industrial AI and analytics to life for operators, engineers, and executives across multi-tiered organizations. Key Responsibilities ● Design and implement enterprise-grade full-stack applications that blend data analytics, BI, and AI insights into seamless user experiences. ● Lead UI/UX design and development for user-defined dashboards, adaptive workflows, and domain-specific visualizations. ● Build multi-layered persona-driven interfaces that adapt to organizational roles—from plant operators to corporate executives. ● Develop graph-based interaction models and visual tools that enable exploration of connected data, such as equipment hierarchies, supply chains, or asset relationships. ● Integrate with data pipelines, APIs, and backend systems to surface real-time industrial data and machine learning outputs. ● Translate complex analytical results into intuitive and actionable visual elements (e.g., alerts, KPIs, scenario simulators). ● Ensure high usability and performance of applications across devices and environments, especially in operational settings. ● Collaborate with stakeholders to validate use cases, iterate on designs, and drive feature adoption. ● Maintain engineering quality through testing, CI/CD integration, and agile collaboration. Required Qualifications ● 6+ years of experience in full-stack or front-end engineering with strong UI/UX sensitivity. ● Proven track record delivering modern enterprise applications with a focus on analytics, decision support, or industrial workflows. ● Expertise in React, TypeScript, modern JavaScript, and visualization libraries (e.g., D3.js, Plotly, ECharts). ● Backend experience with Node.js, Python (FastAPI or Flask), or Java, and integration with REST/GraphQL APIs. ● Familiarity with graph-based UI patterns and libraries (e.g., Cytoscape.js, Sigma.js, Neo4j visual tooling). ● Experience integrating with BI and AI systems, including dashboard frameworks, ML outputs, and embedded analytics. ● Understanding of user-centered design, accessibility, and responsive design principles. ● Knowledge of data handling (structured, semi-structured) and API integration for time-series, events, or industrial telemetry. ● Excellent communication skills and a strong ability to bridge the gap between engineering, design, and domain experts. Preferred Qualifications ● Prior experience in the process industries, industrial automation, or manufacturing systems. ● Familiarity with multi-tenant, role-based applications supporting enterprise hierarchies. ● Exposure to design systems and frameworks like Material UI, Ant Design, or custom component libraries. ● Understanding of security, auditability, and scalability in enterprise software environments. ● Experience with deployment on cloud-native platforms (AWS, Azure, GCP) and containerized environments (Kubernetes, Docker).

About the Role We are seeking a Data Scientist with deep expertise in both classical machine learning and Generative AI to drive digital transformation in the process industries, including energy, chemicals, manufacturing, and industrial automation. You will work on high-impact use cases such as predictive maintenance, process optimization, supply chain forecasting, and intelligent automation—leveraging massive industrial datasets, domain-specific knowledge, and cutting-edge AI/ML techniques. Drawing inspiration from the work done at AspenTech, Aveva, Siemens, C3.ai, and Palantir, you will lead the development and deployment of production-grade models that create measurable business value for mission-critical operations. Key Responsibilities ● Design, develop, and deploy advanced machine learning and deep learning models for predictive analytics, anomaly detection, optimization, and simulation in process industries. ● Lead the application of Generative AI (LLMs, foundation models) to use cases such as natural language querying of industrial data, automated reporting, operator assist, and control recommendations. ● Collaborate with SMEs, engineers, and product teams to define high-impact use cases grounded in operational and engineering realities. ● Work with large-scale industrial time-series, sensor, and historian data (e.g., OSIsoft PI, Aspen IP.21). ● Build and evaluate digital twins for industrial assets and processes, including physics-informed ML models. ● Apply techniques such as reinforcement learning, probabilistic modeling, and graph learning where applicable. ● Stay current with the GenAI and ML research landscape, and translate breakthroughs into practical solutions. ● Contribute to data pipelines, model monitoring, retraining strategies, and deployment using MLOps tools and platforms. ● Communicate results and insights clearly to both technical and non-technical stakeholders. Required Qualifications ● 1~3+ years of experience in applied data science, with a strong track record of delivering real-world ML/AI solutions. ● Deep understanding of supervised/unsupervised learning, time-series analysis, and generative models (e.g., transformers, diffusion models). ● Experience working with industrial datasets and process industry platforms such as Aveva, AspenTech, Honeywell, or Siemens Xcelerator. ● Proficiency with Python, ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow), and GenAI frameworks (e.g., LangChain, HuggingFace, OpenAI APIs). ● Familiarity with MLOps tooling such as MLflow, Airflow, SageMaker, or Azure ML. ● Strong analytical and problem-solving skills with the ability to work across messy and heterogeneous data sources. ● Solid grounding in statistics, optimization, and experimental design. ● Excellent communication and collaboration skills, with the ability to partner with engineers, domain experts, and executives. Preferred Qualifications ● Background in chemical, mechanical, or process engineering ● Experience with digital twins, control systems, or simulation tools (e.g., Aspen Plus, gPROMS). ● Knowledge of graph data models, semantic layers, or ontologies used in industrial contexts. ● Understanding of domain-specific regulatory, safety, and operational requirements. ● Experience with secure and scalable AI deployment in enterprise or OT/IT hybrid environments.

About the Role We are seeking a Systems Engineering Architect to lead the design, implementation, and operational excellence of our large-scale distributed systems infrastructure. This role is critical in driving architectural decisions and ensuring reliability, scalability, and performance across our platform. You will work cross-functionally with product engineering, DevOps, SRE, and support teams to evolve the foundational systems that power our data pipeline, RDBMS solutions, container-based microservices, and cloud-native deployments. Key Responsibilities ● Architect and design large-scale distributed systems across major cloud service providers (AWS, Azure, GCP). ● Drive the strategy and execution of data infrastructure leveraging Postgres, Elasticsearch/ELK, Snowflake, and Databricks. ● Design and scale distributed data ingestion systems using Kafka or RedPanda. ● Lead the integration of CI/CD systems and automation pipelines. ● Guide the implementation and evolution of containerized microservices on Kubernetes across Linux and Windows environments. ● Own production infrastructure scalability, resiliency, and high availability strategies. ● Implement and optimize observability solutions, including logging, monitoring, and metrics systems. ● Conduct deep performance tuning and capacity planning across application and database tiers. ● Lead incident escalation, conduct root cause analysis (RCA), and drive continuous improvement for production reliability. ● Collaborate with internal stakeholders to balance architecture excellence with pragmatic delivery timelines. Required Qualifications ● 3+ years of experience in systems engineering, with at least 5 years in an architectural or technical leadership role. ● Proven experience designing and operating systems at cloud-scale across AWS, Azure, or GCP. ● Deep expertise in large-scale RDBMS (Postgres preferred) and Elastic Stack (ELK), with working knowledge of Snowflake and Databricks. ● Hands-on experience building and managing data streaming pipelines using Kafka or RedPanda. ● Proficiency in container orchestration using Kubernetes, and managing microservices at scale. ● Strong background in both Linux and Windows systems engineering. ● Track record of leading production-grade CI/CD and deployment automation strategies. ● Deep understanding of monitoring, metrics, and alerting systems (e.g., Prometheus, Grafana, Datadog). ● Exceptional debugging, performance tuning, and troubleshooting skills in large-scale environments. ● Demonstrated experience with RCA and handling critical production escalations under pressure. Preferred Qualifications ● Experience in security-conscious or regulated environments (e.g., financial services, healthcare, government). ● Familiarity with Infrastructure as Code (IaC) tools like Terraform, Pulumi, or CloudFormation. ● Contributions to open-source infrastructure or systems projects.