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Develop B2B2C e-Commerce Platform with latest technologies Be a teammate in a highly dynamic and innovative team in Agile/Scrum approach 使用最新技術開發 B2B2C 電子商務平台 使用 Agile/Scrum 方法，希望您加入我們成為充滿活力與創新精神團隊的一員 Job responsibilities: 1. Establish communication and cooperation with the leadership team and various departments, promote and guide developers to carry out developer work, and be responsible for project planning, online maintenance, etc.2. Support the role of technical backbone in the development team, bear the reality of core technology, and solve technical problems in the development process.3. Conduct system analysis and design according to user needs, provide relevant solutions, and write relevant design and development documents.4. Maintenance and optimization of different systems used in different locations, and solved the technical problems encountered by the development team.5. Perform ad-hoc tasks assigned by management. 1.與領導團隊及各部門建立溝通與合作關係，推動並引導開發人員執行開發相關工作，負責專案規劃、上線維運等事項。2.擔任開發團隊中的技術骨幹角色，承擔核心技術的實作工作，並解決開發過程中的技術問題。 3.根據使用者需求進行系統分析與設計，提出相關解決方案，並撰寫設計與開發相關文件。 4.負責不同地點所使用系統的維護與優化，並協助解決開發團隊遇到的技術問題。 5.執行主管交辦任務。

Key Responsibilities● Work with product owners and other development team members to determine new features and user stories needed in new/revised applications or large/complex development projects● Participate in code reviews with peers and managers to ensure that each increment adheres to original vision as described in the user story and all standard resource libraries and architecture patterns as appropriate● Respond to trouble/support calls for applications in production in order to make quick repair to keep application in production● Participate in all team ceremonies including planning, grooming, product demonstration and team retrospectives● Mentor less experienced technical staff; may use high end development tools to assist or facilitate development process● Advanced proficiency in Object Oriented Design (OOD) and analysis. Advanced proficiency in application of analysis/design engineering functions. Advanced proficiency in application of non-functional software qualities such as resiliency, maintainability, etc. Advanced proficiency in advanced behavior-driven testing techniquesOur Stack● Application Framework: Java 8, Spring Boot● Microservices: Spring Cloud (Spring Cloud Config / Open Feign / Spring Cloud Hystrix / Spring Cloud Gateway)● Database: MySQL (Aurora / RDS)● Public Cache: ElastiCache, Redis (MS, Sentinel, cluster)● Message Queue: Apache RocketMQ, RabbitMQ, Kafka● Coordinator: Zookeeper● APM: Jaeger, opentracing● Documentation: Springdoc-OpenAPI● Search and Reporting: ElasticSearch● Log Real-time Visualization: ELK, Loki● Monitoring: Prometheus, Grafana, CloudWatch● Container: Docker, Kubernetes● CI/CD: Jenkins, ArgoCD

AI Engineering LLM Applications | Senior AI Engineer / Tech Lead - TL (Global Financial Group | Fluent English Required) Company Overview Our client is the Taiwan entity of a well-established global financial group with operations across multiple international markets. The organization is known for its strong governance, financial stability, and long-term commitment to technology-driven transformation. In recent years, the company has made significant investments in AI and data-driven initiatives, forming a dedicated AI team focused on delivering production-ready AI solutions that directly support core business operations and customer-facing platforms. This role involves frequent collaboration with overseas teams, making strong English communication skills essential. Responsibilities Lead AI Engineers and Software Engineers to design and deliver AI-powered solutions Apply Machine Learning and LLM technologies to real-world business systems (e.g., call center, telesales, customer interaction and call routing platforms) Collaborate closely with global stakeholders to understand requirements and drive execution Design, build, and maintain scalable, reliable, and secure AI services Ensure high code quality, system performance, and long-term maintainability Contribute to technical decisions, architecture design, and best practices Balance evolving priorities while maintaining delivery momentum Technologies Python (production-grade development) Machine Learning / Deep Learning(PyTorth, TensorFlow) Large Language Models (LLMs) Generative AI FastAPI, Uvicorn Docker, Kubernetes Distributed, high-throughput, low-latency system architectures CI/CD and cloud deployment experience is a plus

在 Pinkoi，工程師的任務是讓每個來 Pinkoi 的人都能擁有難以忘懷的使用體驗，你必需擁有極大的熱情，因為我們相信一個令人讚賞的網站服務，是由背後每一位工程師努力的追求卓越，每一個小細節都是 Pinkoi 非常在乎的事情！Pinkoi 致力於打造流暢且量身打造的探索與購物體驗，讓顧客輕鬆發現感興趣的商品、品牌與內容，並加深與平台的連結。同時運用創新的 AI 技術與深厚的產業知識，幫助品牌提升銷售業績、使規模快速成長，成為設計品牌邁向規模化、國際化不可或缺的重要夥伴。工作內容與挑戰維護和迭代網站底層架構，包括正式環境和開發環境，例如：CI/CD 流程、程式語言迭代、資料庫架構調整...等。協助建立與優化內部平台工具，提升開發者體驗。設計與維護監控、告警與可觀測性（logging / metrics / tracing）。產出高品質、穩定、可維護且可讀性高的程式碼，並養成良好的自動化測試習慣。能夠順暢地與各種領域的夥伴溝通合作，例如前端工程師、後端工程師、App 工程師、資料工程師等。擁有快速辨識系統問題的能力，並且能夠確實修復問題。持續改善系統架構、效能與穩定性，並樂於撰寫技術文件、分享知識，提升產品開發體驗。持續研究並導入新技術（如 Cloud Native 工具、AI 輔助開發）與創新想法，並評估其在實際環境中的落地與價值，創造更大的影響力。我們希望你有的特質充滿熱情，你想要做出世界級一流的產品。樂於學習，對於新技術抱有好奇以及開放的態度。良好溝通，能夠清晰地和 Pinkoi 的夥伴們溝通你的想法。主動積極，能發掘系統上的不足或可以更好的地方，並提出改善作法。自我要求，具備高標準、時限觀念和責任感。應徵條件有 2 年以上後端開發經驗，具備開發與維護系統的能力。具備良好的程式基礎，並樂於持續精進（Pinkoi 主要使用 Python，但我們歡迎任何程式語言的使用者來應徵）。對資料庫、資料結構以及演算法有基礎的理解，知道它們如何影響你的程式效能。對 Linux 作業系統有基礎的理解，特別是針對 Process 跟 Thread 的部分。熟悉 container 相關技術（例如：Docker、Kubernetes）。加分條件應用程式效能校調相關經驗。具備 Observability 相關經驗（Prometheus, Grafana, OpenTelemetry）。熟悉使用如 MySQL、Elasticsearch、Redis 等常見服務，並了解在設計與開發中需針對其分散式特性（如一致性、可用性、效能瓶頸）做出相應考量。熟悉以 LLM 工具輔助開發，並整合至日常工作中以提升效率與品質。熟悉雲端平台與基礎設施維運（AWS / GCP / Kubernetes / CI/CD pipeline）。熟悉 Cloud Native, Kubernetes 生態系（Helm, ArgoCD, Operators 等）。＃不用想了，趕快來當個 Pinkoi 人如果你有信心能夠勝任這份工作，歡迎提供你的個人履歷及小作業回答，即刻應徵！

Responsibilities1. Develop and implement machine learning algorithms and collaborated with cross-function teams, including product, backend teams, and domain experts to optimize clinical and diagnosis workflow. 2. Deploy machine learning algorithms to aetherAI products, including the web-based platform and edge devices. 3. Engage in medical imaging research using machine learning techniques with physicians and teams to solve real-world problems.Minimum Qualifications 1. Experience in machine learning, data mining, statistical modeling, and software design. 2. Fluent in Python programming, including general packages such as NumPy, and deep learning frameworks such as TensorFlow / PyTorch. 3. Familiarity with Linux/Unix environments, Docker, and Git. 4. Good communication and presentation skills.

公司描述 我們是台灣領先的人力資源管理系統提供商，旗下產品已穩定服務市場多年，協助數千家企業實現數位轉型。我們不滿足於現狀，致力於透過技術創新，將深耕多年的穩定系統推向更高的效能境界。 職位亮點 ✅ 技術架構的推手與導師：您將負責核心功能的架構規劃與 Code Review，您的技術見解將直接影響團隊的開發品質與成長。 ✅ 全方位的產品參與度：從需求分析、可行性評估到系統規劃與開發，您將與 PM 及跨部門團隊緊密協作，對產品擁有高度的參與感與影響力。 ✅ 現代化技術與維運並重：除了精進 PHP 技術，也強調 Docker 容器化部署、非同步處理與 NoSQL 的實踐，讓您在維護穩定性的同時，持續應用現代化開發技術。 ✅ 開放且支持成長的文化：我們鼓勵主動積極的技術分享，提供一個既有挑戰性又有團隊支持的環境，讓您的技術成就感與產品價值同步提升。 職位職責 🔹 系統架構規劃與開發：負責核心功能的架構設計，確保系統具備高度的安全性、可擴展性與維運彈性。 🔹 技術引領與品質把關：協助團隊進行技術指導與 Code Review，分享開發經驗並建立優質的代碼規範。 🔹 效能優化與歷史系統維運：針對現有系統進行深入的效能優化與異常排除，確保長年運行的服務依然能保持高效穩定。 🔹 需求分析與跨部門協作：與 PM 深入討論產品需求，分析項目可行性，並與前端、QA 合作推動功能落地。 🔹 現代化工作流實踐：利用非同步處理、Queue 工作流與 Docker 技術，優化開發、測試與部署流程。 職位要求 ✔ 3 年以上 PHP 後端開發經驗，熟悉至少一種框架（如 CodeIgniter, Laravel, Yii）。 ✔ 精通資料庫設計與調優：擁有豐富的 MySQL 表結構設計與 SQL 效能優化實戰經驗。 ✔ 具備 Mentor 或帶領團隊經驗：能指導他人、進行 Code Review 並樂於分享技術知識。 ✔ 深厚的系統設計基礎：熟悉 API 設計原則、非同步處理、背景任務（Queue）及 NoSQL 資料庫（如 Redis, MQ）應用。 ✔ 具備容器化開發經驗：熟練使用 Docker 進行環境開發與快速部署。 ✔ 具備基礎全端能力：熟悉 HTML、JavaScript、jQuery 等前端技術。 ✔ 特質要求：主動積極、解決問題導向，具備架構思維與良好的跨部門協作溝通能力。 加分條件： 具備大型專案管理經驗或熟悉敏捷開發 (Agile) 流程。具備網絡架構、伺服器管理或系統架構重構的優化經驗。擁有產品從 0 到 1 或從舊架構遷移至新架構的實務案例。 ---------------------------------------------------------------------- 若您對此職位感興趣，請立即聯繫，讓我為您介紹更多詳細資訊！ ▶︎ 聯繫人：招募顧問 Owen Wu▶︎ LINE： https://line.me/ti/p/ICjS8Jx0Dq▶︎ LinkedIn： https://www.linkedin.com/in/owen-wu-1023a41a4/

About the Role We’re looking for a Senior AI Algorithm Engineer with a strong background in image processing and vision-language AI. You will lead the design and optimization of cutting-edge computer vision and inference algorithms, with applications spanning color analysis, image stitching, and multimodal understanding. This role requires hands-on experience in deep learning, cloud deployment, and production-level AI integration. You’ll also work with frameworks such as NVIDIA NeMo and deploy AI services using NIM to cloud platforms like GCP and AWS, with Kubernetes for orchestration. What You’ll Do Design and implement deep learning models for image processing, object detection, and anomaly detectionDevelop models for color recognition, color classification, and image-based feature analysis Fine-tune or integrate Large Language Models (LLMs) for vision-language tasks such as captioning, semantic search, and classification Optimize models for accuracy, inference speed, and resource efficiency Deploy and scale model services on GCP / AWS using Kubernetes (K8s) Utilize NVIDIA NeMo to train and deploy LLMs or VLMs, and package models into lightweight Docker containers served via NIM architectureCollaborate closely with product, frontend, and backend teams to integrate AI features into real-world applications

【職務核心】 您將利用海量數據構建核心決策模型，透過自動化手段解決內部的營運痛點。我们需要您具備將數學理論轉化為生產級 (Production-grade) 程式碼的能力。 數據煉金：使用 SQL 從龐大的資料倉儲中萃取 (Extraction) 有價值的特徵，並進行深度分析。模型開發與自動化：應用 Data Mining 與 ML 技術設計自動化工具，優化內部作業流程與決策效率。落地與維運：負責模型的容器化 (Docker) 封裝與部署，監控模型在正式環境的表現，確保系統的高可用性。技術顧問：與跨部門團隊協作，向非技術人員解釋 AI 模型的應用場景與邊界 (Limitations)。

【關於這個角色】核心任務是打通 LLM 與應用程式之間的溝通橋樑。你需要使用 Java 實作 Model Context Protocol (MCP Server)，讓 AI Agent 能夠安全、標準化地存取我們的資料與工具。 【你將面臨的挑戰】 Protocol Implementation: 開發與優化 MCP Server，確保與 LLM Client 端的通訊順暢且低延遲。Backend Development: 負責 API 的設計與實作，處理複雜的資料流邏輯與外部 API 整合。System Stability: 透過 Docker 容器化技術確保環境一致性，並透過完整的測試代碼（Unit/Integration Test）保障系統品質。

🏢 Full-Stack Software Engineer (AI × Safety Tech) Location: Taipei / Taoyuan (Hybrid Remote) Job Type: Full-time Compensation: Competitive base + performance bonus (negotiable based on experience) Seniority: Mid to Senior (4–6 years) 🎯 Responsibilities 🛠 Product Development Build and iterate the core SAFE platform used in smart pool / open-water / port safety systems. Frontend development for operator dashboards: maps, zone overlays, live streams, alerts, events, and reports. Backend development of REST/gRPC APIs and real-time WebSocket services integrating: AI inference pipelines ePTZ tracking modules RTSP/ONVIF camera streams NVR / VMS systems Design of event stream pipelines using Kafka / MQTT / RabbitMQ for real-time alerts and post-recording workflows. 🔗 System Integration Collaborate with AI engineers to define inference APIs, score thresholds, and versioning (incl. A/B testing). Work closely with field engineers (FAEs) and hardware partners on-site deployments: cameras, edge boxes (GPU), ePTZ, and network topology. ⚙️ Deployment DevOps (DevOps/SRE) Build reproducible cloud + edge environments using Docker, K8s, Helm, Terraform. Own the CI/CD pipelines (GitHub Actions or GitLab CI): release management, automated testing, rollback procedures. Monitor system health: Prometheus/Grafana, ELK/OpenSearch, Sentry for logs, metrics, and availability. 📦 Productization Customer Success Parameterize site-specific configs (alert levels, whitelist/blacklist, camera/network setup, sensitivity). Author technical documentation, setup guides, and support field testing or PoC if needed. ✅ Requirements (Must-Have) 4–6 years of hands-on web product development experience. Able to own features from spec → design → implementation → deployment → maintenance. Frontend: TypeScript + React (or Vue). Familiar with WebSocket, HLS, WebRTC basics. Backend (proficient in at least one, and can quickly learn others): Go (Golang): Gin/Fiber or similar Node.js: Express/NestJS Python: FastAPI Solid API design, database schema modeling, and testing skills. Databases: PostgreSQL, Redis (caching, job queues, Pub/Sub). DevOps: Docker, basic Kubernetes, CI/CD experience (GitHub Actions or equivalent). Streaming: Familiarity with RTSP/ONVIF, NVR/VMS playback and access control. Collaboration: Ability to communicate across AI/FAE/PM teams and decompose fuzzy specs into shippable tasks. ⭐ Bonus Points (Nice-to-Have) Required: Completion of at least one cybersecurity-related training or certification, e.g.:ISO 27001 internal auditor courseCloud security foundation (AWS/GCP)Complex audits (e.g. penetration testing, CVE remediation) are handled externally; you’ll only need to apply fixes and adjust configs as needed. Real-time low-latency streaming: WebRTC, FFmpeg, HLS/DASH experience. Kafka / MQTT event stream experience. ONVIF PTZ camera control, multi-camera stitching. Infrastructure-as-Code: Terraform, Helm, Kustomize. Observability: Alert rule design (e.g., latency, packet loss, GPU usage, noise suppression). Language: Ability to read/write technical English; conversational Japanese is a plus (for overseas partner support).