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公司介紹 這是一家獲得 NVIDIA 直接投資、Computex 唯一點名 的台灣新創公司，專注於 3D 數位孿生（Digital Twin）與 AI 模擬技術。他們的核心願景，是讓 AI 不只存在雲端，而能在真實世界中運作——成為「實體 AI (Physical AI)」的推進者。 他們的技術能將 CAD 檔案在短時間內轉換成高擬真的 3D 虛擬工廠，結合 AI 模型模擬生產流程，幫助半導體與製造大廠快速測試與優化產線布局。這家公司在短短兩年內，即與全球科技巨頭展開合作，並在 NVIDIA 創辦人黃仁勳的 Keynote 中多次被點名。 目前團隊正邁入「技術產品化」關鍵階段，準備將實驗室成果轉化為可大規模商用的平台。這個職位將是其中的關鍵推手。 工作內容 作為資深全端工程師，你將與產品、AI、3D 與設計團隊密切合作，將複雜的技術能力轉化為清晰、直覺且高效的產品體驗。 你的工作將包含： 參與產品從 0→1 的系統架構設計與開發 將複雜的技術能力轉化為易於理解與操作的產品介面 與 Product / Design 團隊合作，平衡 UX、技術可行性與系統擴展性 設計與維護前後端 API、資料模型與即時通訊架構 建立可重用的 UI Pattern、Component 與 Design System 整合 AI、3D Simulation 與平台功能，打造一致的產品體驗 參與企業級平台與工具型產品的 UX 與互動設計 使用的技術 Frontend：React / Vue / Next.js Backend：Python / Node.js API Design / System Architecture Real-time Communication Data Visualization 3D / Simulation / Web-based UI AI Simulation Platform Integration （團隊也會接觸 NVIDIA Omniverse 等 3D simulation 生態）工作地點 台北市南港區（Hybrid 工作模式） 每週固定一天遠端工作 + 每年 20 天彈性遠端

公司介紹 這是一家高速成長的 AI 新創團隊，專注於 Physical AI 與 Industrial AI 的落地應用。團隊致力於打造能將真實世界工業環境快速轉換為高擬真模擬場景的 AI 平台，讓 AI 能在虛擬環境中進行訓練與策略優化，最終部署至真實工業系統。 公司產品結合 3D Simulation、Digital Twin 與 Reinforcement Learning 技術，讓企業可以在虛擬世界完成複雜系統的訓練與測試，大幅降低現實環境的成本與風險，並加速智慧製造與自動化的導入。 團隊由多位具創業與深度技術背景的成員組成，目前已獲得 國際級 AI 科技公司與知名投資機構支持，並與高端製造及半導體產業合作。工程師將有機會參與 AI + Simulation + Robotics 的前沿技術應用，直接將研究級技術落地至真實世界場景。 工作內容 作為 Senior Reinforcement Learning Engineer，你將負責透過強化學習技術優化自動化系統與工業場景中的 AI 決策能力，並在模擬環境中訓練可部署於真實世界的 AI 模型。 你將有機會參與 AI 在 工業自動化、機器人與智慧製造場景中的實際應用。 主要職責包含： 在 NVIDIA Isaac Sim 等模擬平台上建立與訓練強化學習模型 設計並實作 state space、action space 與 reward function 開發與優化 RL policy（如 Q-learning / Policy-based methods） 與 AI / Simulation / 3D 團隊合作進行系統模擬與模型訓練 持續調整模型與參數，提升策略效率與系統穩定度 將模擬環境中的最佳策略導入實際工業系統 使用技術 Python PyTorch / TensorFlow Reinforcement Learning Algorithms NVIDIA Isaac Sim Simulation / Digital Twin Robotics / Automation Systems

公司介紹 我們的客戶是一家專注於 Physical AI 與數位孿生（Digital Twin）技術 的 AI 新創團隊，致力於打造能夠讓 AI 在虛擬環境中訓練、學習並優化決策的下一代平台，並將最佳策略部署回真實世界場域。 團隊核心技術結合 AI、3D 模擬、運籌優化與大型場域建模，應用於智慧製造、自動化物流與高精密產業等場景，協助企業在虛擬工廠中完成策略模擬與 AI 訓練，大幅提升建置效率與營運決策能力。 公司獲得 國際 GPU 生態系與多家產業資本支持，並與大型科技與製造企業合作，是少數專注於 Sim-to-Real / Real-to-Sim AI 應用落地 的技術團隊。 如果你對 AI + Simulation + Robotics / Automation 的跨領域技術有興趣，這將是一個能直接參與核心產品與演算法設計的機會。 工作內容 你將加入核心演算法研發團隊，負責設計並優化應用於 大型數位孿生場域的演算法模型，協助解決複雜環境中的路徑規劃、排程與資源配置問題。 主要職責包含： 建立與設計演算法模型（如圖論、網格建模、路徑規劃或優化模型） 從 3D 環境與場域資料中建構抽象模型並設計解法 設計並實作高效能演算法模組（Python 為主） 使用 GPU 加速工具優化大型資料處理或模擬效能 與產品與工程團隊合作，將演算法整合至平台系統 測試與評估不同策略表現並持續優化 使用技術 Python CUDA / GPU Parallel Computing PyTorch Algorithm Design / Data Structures Graph Theory / Path Planning 3D Simulation / Digital Twin Optimization / Scheduling

Role Scope Own everything above the Edge AI runtime: cloud backend, web dashboards, public-facing venue displays, smartwatch apps, and the incident workflow engine Connect AI detection to human response, resolution, and audit — the full incident closure loop Not supporting an existing team — building the platform that turns edge AI output into an operational product from scratch Work directly with CEO and CTO to define what to build, then go build it First 6 Months — Deliverables Q1: User Dashboard — Multi-site event management portal with traffic trend analytics, alert accuracy metrics, and evidence package review (snapshots, video, timeline, zone overlay) Venue Display — Public-facing digital signage for facility lobbies showing real-time AI monitoring status, occupancy data, and promotional content rotation. Signage design language, not an ops console Q2: SmartWatch App — Cross-platform wearable app for alert acknowledgment, dispatch, and case closure. One-handed operation, under 2 seconds per critical action Emergency Workflow Engine — Bidirectional event lifecycle engine implementing an 8-state Case Workflow State Machine (Queued → Needs Confirm → Validated → Rejected → Dispatched → Escalated → Closed → Audit Pending) with SLA timers, timeout escalation, and dispatch routing Backend Build Event Ingest API receiving structured JSON and evidence payloads from edge devices via IPSec/WireGuard VPN Implement GCP Pub/Sub event streaming with dual storage: BigQuery for time-series analytics, Postgres for operational state Develop Workflow State Machine covering the full 8-state case lifecycle with configurable SLA timers, timeout escalation triggers, and dispatch routing logic Build multi-tenant management layer: sites, users, roles, and permissions Implement notification hub spanning LINE, email, webhook, and smartwatch push Expose RESTful and WebSocket APIs serving all three client surfaces (dashboard, display, watch) Frontend Web Dashboard — Real-time event feeds, historical analytics charts, event detail views with evidence packages, and a CMS module for Venue Display content management Venue Display — Large-screen optimized rendering with automatic offline fallback and local caching when cloud connectivity drops SmartWatch App — Cross-platform compatibility targeting Wear OS native or web-based approach; technology choice is yours to make and defend Infrastructure Manage GCP project end-to-end: Cloud Run, Pub/Sub, BigQuery, Cloud SQL, Cloud Storage Build and maintain CI/CD pipelines for all cloud services Implement fleet-wide monitoring, alerting, and health dashboards across all deployed sites Handle OTA content delivery for Venue Display Tech Stack Edge (interface with, not own) — NVIDIA Jetson Orin Nano, DeepStream, YOLO + VLM pipeline. Pushes structured event JSON + evidence packages via IPSec/WireGuard VPN Cloud / Backend — GCP (Pub/Sub, Cloud SQL/Postgres, BigQuery, Cloud Run). Python or Node.js. WebSocket for real-time streaming Frontend — React or Vue (pick one and commit). Data visualization library. Responsive dashboard + signage-optimized display Wearable — Wear OS native or cross-platform. BLE/WiFi connectivity within facility networks Requirements — Must Have 3+ years shipping production web applications end-to-end (backend + frontend + deployment) Track record of building cloud backends from scratch, not just adding features to existing systems Hands-on experience with at least one major cloud platform: GCP, AWS, or Azure (we use GCP) Real-time systems experience: WebSocket, event-driven architecture, Pub/Sub or message queues Relational database design and query optimization (Postgres preferred) Proficiency in both Python and JavaScript/TypeScript At least one shipped mobile or wearable application in production Requirements — Strongly Preferred Workflow or state machine system development (ticket systems, dispatch engines, approval flows — anything with lifecycle states and timeout logic) Video/media handling: HLS streaming, thumbnail generation, evidence packaging Prior experience owning a full product surface at a startup with fewer than 10 people GCP-specific hands-on: Pub/Sub, Cloud Run, BigQuery Mandarin fluency for internal communication + English technical reading proficiency Requirements — Nice to Have IoT or edge integration experience (MQTT, device management, OTA) Digital signage or kiosk application development Background in safety/compliance systems, incident management, or operational workflows

We are seeking a Senior Embedded Systems Software Engineer with strong Embedded Linux experience to join our engineering team. You will design, build, and maintain the software that powers our NVIDIA Jetson–based edge AI cameras — including Python application code, system services, OTA update mechanisms, networking, and device reliability.This is a hands-on engineering role focused on Linux systems and product software running on resource-constrained devices. You will not be working on MCU firmware or low-level hardware bring-up. Instead, you'll operate across the OS and application stack to ensure our camera systems are robust, secure, and easy to deploy at scale.If you enjoy building software for real hardware, solving complex debugging challenges, and owning features end-to-end, we would love to speak with you.What you will do-Develop and maintain system-level and application-level software for reliability in the field for our edge AI devices-Implement and own OTA for our deployed device fleet-Write Python application code for device control, edge logic, monitoring, and data flows-Work with C/C++ components for performance-critical functionality-Debug Linux systems involving multiple services, containers, and custom applications-Tune performance across the stack: kernel, services, containers, and user applications-Use Docker containers for packaging and deploying edge software components-Collaborate with hardware vendors to diagnose and resolve system-level issues-Work with backend/API teams to maintain reliable device–server communication-Mentor the team through code review, coaching, and general feedbackWhat we are looking for-Bachelor's or Master's in Computer Science, Electrical Engineering, or related field-5-7+ years of experience in Linux-based embedded systems or systems software-Solid C++ skills in a Linux environment and/or Python development experience-Experience with SBC or Embedded Linux platforms-Understanding of networking fundamentals (TCP/IP, routing, TLS/HTTPS, certificates)-Experience debugging Linux applications and services (systemd, logs, containers)-Experience with Docker containerization-Strong problem-solving skills and independent ownership mindset-Clear communication and collaboration skillsNice to have-Experience implementing OTA systems or device-update workflows-NodeRED, Flask, or REST API development-Industrial automation background (PLC ladder logic, Structured Text)-Industrial protocols: EtherNet/IP, Profinet, Modbus, RS232, RS485, CANbus-Experience with OpenCV, GStreamer, or real-time video processing-Experience with FTP/SFTP/SMB, NTP synchronization, or device-to-server messaging-Experience with fleet management of edge devicesWhy join-Build core systems that directly impact real-world manufacturing-High ownership and autonomy-Work closely with hardware, AI, and customer-facing teamsJoin a fast growing, fast moving and profitable startup

We are seeking a Staff Embedded Systems Software Engineer with strong Embedded Linux experience to join our engineering team. You will design, build, and maintain the software that powers our NVIDIA Jetson–based edge AI cameras — including Python application code, system services, OTA update mechanisms, networking, and device reliability.This is a hands-on engineering role focused on Linux systems and product software running on resource-constrained devices. You will not be working on MCU firmware or low-level hardware bring-up. Instead, you'll operate across the OS and application stack to ensure our camera systems are robust, secure, and easy to deploy at scale.If you enjoy building software for real hardware, solving complex debugging challenges, and owning features end-to-end, we would love to speak with you.What you'll do-Develop and maintain system-level and application-level software for reliability in the field for our edge AI devices-Implement and own OTA for our deployed device fleet-Write Python application code for device control, edge logic, monitoring, and data flows-Work with C/C++ components for performance-critical functionality-Debug Linux systems involving multiple services, containers, and custom applications-Tune performance across the stack: kernel, services, containers, and user applications-Use Docker containers for packaging and deploying edge software components-Collaborate with hardware vendors to diagnose and resolve system-level issues-Work with backend/API teams to maintain reliable device–server communication-Mentor the team through code review, coaching, and general feedbackWhat we're looking for-Bachelor's or Master's in Computer Science, Electrical Engineering, or related field-8-10+ years of experience in Linux-based embedded systems or systems software-Solid C++ skills in a Linux environment and/or Python development experience-Experience with SBC or Embedded Linux platforms-Understanding of networking fundamentals (TCP/IP, routing, TLS/HTTPS, certificates)-Experience debugging Linux applications and services (systemd, logs, containers)-Experience with Docker containerization-Strong problem-solving skills and independent ownership mindset-Clear communication and collaboration skillsNice to have-Experience implementing OTA systems or device-update workflows-NodeRED, Flask, or REST API development-Industrial automation background (PLC ladder logic, Structured Text)-Industrial protocols: EtherNet/IP, Profinet, Modbus, RS232, RS485, CANbus-Experience with OpenCV, GStreamer, or real-time video processing-Experience with FTP/SFTP/SMB, NTP synchronization, or device-to-server messaging-Experience with fleet management of edge devicesWhy join-Build core systems that directly impact real-world manufacturing-High ownership and autonomy-Work closely with hardware, AI, and customer-facing teams-Join a fast growing, fast moving and profitable startup

AI 生成模型專家，加入智慧物流/製造的未來🤖 公司介紹 我們是一家新創公司，致力於融合 3D 數位孿生Technology 與 AI 生成模型（Generative Model），為企業提供 AI SAAS 軟體垂直解決方案。我們是 NVIDIA Inception Program 的成員，也是 NVIDIA 的策略夥伴。技術已獲得 NVIDIA 創辦人兼執行長黃仁勳的公開肯定，並在智慧物流中心的建立上獲得了顯著成就。目前也已有穩定的客戶合作中 工作內容 我們正在尋找一名具備電腦視覺專長的資深AI工程師，此職位將與 3D美術設計師密切合作，共同建立高價值的電腦視覺合成資料。這個角色需分析真實樣本、解析樣本特徵模式，並將成果提供給3D美術師作為產生器建立的基礎上。此外，在3D美術設計師各階段產生資料時，需要驗證資料對訓練 AI 的成效，並歸納出資料的改善方向， 一同完善產生器的成效。強化學習工程師將負責利用強化學習技術來優化自動化機械與系統，例如基於強化學習的機器人、自動化系統、控制系統及工業設計的最佳化。該職位需要在NVIDIA Isaac Sim平台上實現包括狀態空間 (state space)、動作空間 (action space)、回饋機制 (reward)、Q-Learning 等所有必要步驟，最終達成工業自動化系統的最佳化目標。▌日常職責（取決於實際具體項目）：在NVIDIA Isaac Sim中建立並設計工業自動化系統的強化學習模型。定義並實作state space、action space、reward function和策略演算法。與其他AI工程師合作，進行系統模擬與測試，持續調整模型參數以提高性能。分析並解決模擬過程中的技術挑戰，確保系統的穩定性與效率。與跨部門團隊協作，理解並轉化業務需求為技術方案。

加入全球頂尖的科技製造服務領導者(上市公司)，參與集團級別的數位轉型「創世紀」計畫，與國際知名顧問公司BCG合作，共同打造AI賦能的未來工廠。您將有機會接觸最前沿的AI、大數據和雲端技術，與Nvidia、AWS、Google等巨頭合作，並直接向高層匯報。我們正在尋找具有遠見、系統思維的技術領袖，引領全球200多個廠房的AI轉型，實現真正的產業變革。專注於 解決方案設計與跨職能協作 職責 架構設計：設計架構模組，並與 IT/OT 組件進行整合。 跨職能協作：與跨職能團隊（如 CiT、BG、IT 和工廠車間）合作，推動應用標準化。 生態合作對接：確保 IT/OT 架構與生態解決方案之間的一致性與匹配性。 知識庫與 Token 相關系統建設：負責知識管理與 Token 管理系統的設計與建置。

LEOTEK 為北美第一大智能交通號誌與道路照明服務提供商，至 1992 年起，服務北美、歐洲、中東、紐澳等 30 多國道路基礎建設 30 餘年，致力道路智動化 AI+ 物聯網維運預警服務解決方案，以安全、生態與低碳為核心，推動城市淨零智能化轉型。【產品與解决方案】1. 戶外照明與交通燈具－LED 路燈、LED 交通號誌燈2. 環境友善照明－人因照明智慧路燈系統、新一代 ECOridge（生態線）生態照明3. 智慧路燈解決方案－智慧路燈控制器4. 道路智動化解決方案－智慧照明與交通解決方案、道路數據蒐集分析平台 我們正在尋找一位對嵌入式系統與AI影像應用充滿熱情的工程師，加入我們的IoT產品開發團隊。此職位將負責基於 NVIDIA Jetson 平台的影像處理與 AI 應用開發，涵蓋從底層驅動、系統整合到應用層開發，並參與產品功能驗證與測試流程。 【工作內容】基於 NVIDIA Jetson Nano / Orin NX 等平台進行嵌入式系統開發與整合開發與移植 Linux 裝置驅動程式，特別是 Camera 相關驅動（V4L2）使用 C++ / Python / Qt 進行應用程式開發與系統整合整合 Camera 模組與 AI 模型，實現影像擷取、處理與推論功能撰寫與維護功能驗證測試程式，協助除錯與效能優化撰寫技術文件與開發紀錄，支援跨部門溝通與技術轉移

職位概述： Black Sesame Technologies 誠邀充滿熱情與才華的專業人士加入我們的團隊，擔任 AI 系統工程師（嵌入式平台）。此職位將讓您有機會參與自動駕駛與機器人領域的前沿技術，並負責在嵌入式平台（如 NVIDIA Orin 上的 TensorRT）上部署 AI 解決方案。我們尋找對學習充滿熱忱、勇於創新並希望在嵌入式 AI 領域發揮專長的優秀人才。 職責： 模型部署： 在嵌入式平台（如 NVIDIA Orin 上的 TensorRT）上部署機器學習模型，專注於自動駕駛與機器人應用。優化與調整： 優化深度學習模型，確保其在嵌入式系統上的最大效能與最低延遲。性能監控與分析： 實作即時性能與功耗監控，並制定持續改進策略。跨團隊協作： 與硬體與工具鏈工程師密切合作，提升軟硬體協同設計（SW/HW Co-Design）的整合度與效能。技術創新： 追蹤 AI、機器學習與 AI 加速器領域的最新技術趨勢，並應用於產品開發。專業指導： 為嵌入式 AI 系統部署提供技術專業指導與解決方案。Position Overview: Black Sesame Technologies is seeking motivated and talented individuals to join our team as AI Systems Engineer (Embedded Platforms). This position offers an exciting opportunity to work on cutting-edge technologies for autonomous vehicles and robotics. We are looking for individuals who are eager to learn, innovate, and contribute to deploying AI solutions on embedded platforms such as TensorRT on NVIDIA Orin. Responsibilities: Model Deployment: Deploy machine learning models on embedded platforms (e.g., TensorRT on NVIDIA Orin) with a focus on applications in autonomous vehicles and robotics.Optimization: Optimize and tune the performance of deep learning models to ensure maximum efficiency and minimal latency.Profiling and Monitoring: Implement real-time performance and power monitoring, and develop strategies for continuous improvement. Collaboration: Work closely with hardware and toolchain engineers to improve SW/HW Co-Design. Innovation: Stay updated on the latest industry trends, technologies, and advancements in AI, machine learning, and AI accelerator. Provide guidance and technical expertise in the deployment of AI systems on embedded platforms.