清大專區

【AITE】(Automation Infrastructure and Tools Engineering) team: provide automation & tools solution to support server design, validation and MFG production. (1) BMC/BIOS/HW/performance test tools and automation (2) MFG L6/L10/L11 etc. test solution (3) Automation test platform development 工作內容: 1.負責伺服器診斷平台於設計驗證（Design Validation, DV）與量產製造（Manufacturing, MFG）階段之整體架構規劃與設計。 2.建立並制定 Diagnostic Platform、Validation Framework、Automation Infrastructure 與測試流程標準。 3.規劃並整合 X86 Server 系統相關診斷方案，涵蓋 CPU、DIMM、NIC、GPU、Switch、PDU、Storage、NVMe 與相關子系統。 4.主導系統架構演進、技術決策與平台最佳化，提升系統可擴展性（Scalability）、可維護性（Maintainability）與穩定性（Reliability）。 5.建立跨 Design Validation 與 Manufacturing 共用之診斷框架與平台架構。 6.與硬體、韌體、軟體、Validation、Manufacturing 及全球研發團隊跨部門合作，制定技術策略與開發標準。 7.提供全球開發團隊技術方向與架構指導，推動跨區域（Cross-Geo / Cross-Site）技術合作與最佳實務建立。 8.評估新技術與新平台需求，制定未來 Server Diagnostic Platform 技術藍圖（Technical Roadmap）。 9.帶領開發團隊落實架構設計，協助解決高複雜度系統問題與平台整合議題。 ※依學經歷、工作年資敘薪 Job Description: 1. Lead architecture planning and design of server diagnostic platforms across Design Validation (DV) and Manufacturing (MFG) environments. 2. Define and establish diagnostic platforms, validation frameworks, automation infrastructure, and testing standards. 3. Architect and integrate diagnostic solutions for X86 server systems, including CPU, DIMM, NIC, GPU, Switch, PDU, Storage, NVMe, and related subsystems. 4. Drive platform evolution, technical decision-making, and system optimization to improve scalability, maintainability, and reliability. 5. Establish unified diagnostic frameworks and shared platform architecture across validation and manufacturing environments. 6. Collaborate cross-functionally with hardware, firmware, software, validation, manufacturing, and global engineering teams to define technical strategies and development standards. 7. Provide technical leadership and architectural guidance to global development teams while promoting cross-geo technical collaboration and best practices. 8. Evaluate new technologies and define future technical roadmaps for server diagnostic platforms. 9. Lead development teams in implementing architecture designs and resolving complex system-level technical issues.

Projects managed by Compal Medical Product Development Division include the following areas: 1.Medical product category 2.Wearable product category 3.Sports, leisure, and entertainment category 4.Smart IoT (Internet of Things) category Firmware Engineer – Key Responsibilities 1.Design -Provide system architecture, perform analysis, and define functional specifications. 2.Implementation -Setup development environment of the embedded systems, including RTOS-based and bare-metal firmware. -Develop, integrate, and maintain bootloader, kernel, GUI, and core firmware functions. -Develop, integrate, and maintain drivers and functions for sensors, motors, and wired/wireless communication. 3.Performance Optimization -Design, implement, and optimize algorithms for system performance. -Define and develop communication protocols. 4.Verification -Create test plans, develop testing tools, and generate detailed test reports. 5.Documentation & Compliance -Prepare and maintain design and technical documentation. -Ensure all processes comply with ISO standards.

1. 負責智慧型裝置產品之主動式（Active Cooling）與被動式（Passive Cooling）散熱方案設計與優化。 2. 參與 RFP/RFQ 階段的 Thermal Solution 規劃，包含可行性評估、效能分析及成本估算。 3. 使用 FloTHERM / Ansys Icepak 建立熱模型，執行熱模擬分析與設計優化。 4. 規劃並執行產品熱測試與驗證，分析 Thermal Performance、進行 Root Cause Analysis，並推動問題改善。 5. 建立及維護 Thermal 相關技術文件，包括 PTS、Thermal Test Plan、Thermal Design Guide 等。 6. 與跨功能研發團隊合作，並研究與評估新型散熱技術、材料及 Thermal Solution，推動未來產品應用 == English == 1. Responsible for the design and optimization of active and passive cooling solutions for smart device products. 2. Participate in RFP/RFQ-stage thermal solution planning, including feasibility assessment, performance evaluation, and cost estimation. 3. Build thermal models and perform thermal simulation, analysis, and design optimization using FloTHERM / Ansys Icepak. 4. Plan and execute thermal testing and validation, analyze thermal performance, conduct Root Cause Analysis, and drive issue resolution and improvement. 5. Develop and maintain thermal-related technical documentation, including PTS, Thermal Test Plans, and Thermal Design Guides. 6. Collaborate with cross-functional engineering teams to research and evaluate new thermal technologies, materials, and thermal solutions for future product applications.

1.系統整合測試： 執行Server整機功能驗證，確保 BIOS、BMC、FPGA 與周邊裝置(NIC, RAID, NVMe, GPU)之相容性與穩定度。 2.OS與驅動程式驗證： 驗證主流作業系統(Ubuntu, RedHat, Windows Server)在不同Kernel版本下的驅動程式相容性，並維護Driver List Baseline。 3.問題除錯與分析： -針對測試中發生的System Hang、Crash、Kernel Panic進行第一線除錯。 -利用Log分析工具(dmesg, SEL, SOL, UART log)釐清問題根源(HW/FW/OS Issue)。 4.Bug追蹤與協作： 撰寫精確的Issue Report，協助RD複製問題並驗證解決方案。 5.測試環境維護： 架設並維護PXE Server、Console Redirect等測試基礎設施。

1. Responsible for handling RFQ/RFI and NPI phase or MP phase quotations, logistics planning, and resolving unexpected issues to ensure schedule adherence. 2. Collaborate with cross-functional teams to ensure timely transition of projects into mass production. 3. Build and maintain strong working relationships with customers. 4. Review operational processes and identify optimal solutions to improve efficiency. 5. Track and analyze improvement opportunities through weekly reviews. 6.Prepare and deliver customized sales presentations tailored to specific client needs. ※依學經歷、工作年資敘薪

【AITE】伺服器Diag開發工程師（BMC/BIOS/HW） 工作內容： AITE(Automation Infrastructure and Tools Engineering) team: provide automation & tools solution to support server design, validation and MFG production. (1) BMC/BIOS/HW/performance test tools and automation (2) MFG L6/L10/L11 etc. test solution (3) Automation test platform development 此職位主要使用 Python 進行 BMC/BIOS/HW 測試案例自動化。 ※依學經歷、工作年資敘薪 CS or EE Master/Bachelor with 0~3 years experience (工A) CS or EE Master/Bachelor ＞ 3 years experience (高工級) CS or EE Master/Bachelor ＞ 5 years experience (課長級)

1. 3D列印 : 協助3D列印工件修整、噴漆、組裝 2. NC : 協助工件掃面上機台、工件毛邊修整、殘膠去除、攻牙 3. 後處理 : 協助工件研磨、噴漆、拋光、印刷、組裝 4. 執行主管交辦事項 ※無經驗可 ※學年實習，需每周出勤至少3.5天 ※可配合實習學分簽約

1.車用電子產品客戶開發與業務拓展 2.車用電子產品市場分析及行銷策略規劃 3.善於跨部門溝通，負責客戶與研發團隊之專案執行

1. 零件採購 2. 供應鏈管理 3. 原料成本談判及規劃產能 4. 跨職能及部門合作，與Buyers, R&D, sales, PM...等協作 ※依學經歷、工作年資敘薪

About the role: The AI/ML Test Engineer is responsible for verifying and validating embedded software used in automotive systems. This role ensures that software meets functional, performance, safety, and quality requirements across all stages of the development lifecycle. The position requires strong knowledge of software/machine learning testing methodologies, automotive systems, and embedded software, along with hands-on experience in software test execution and automation. Key Responsibilities: • Design, develop, and execute test cases based on algorithm and machine learning system requirements using Python. • Thermal algorithm and model performance testing: test the object detection model like detection of pedestrians, cyclists and wildlife during harsh environmental conditions, validate that thermal noise sources do not trigger false collision warnings or phantom braking, evaluate model performance under stress conditions or lens occlusion. • Configure and maintain test environments, mainly Software-in-the-Loop and Hardware-in-the-Loop setups. • Identify, document, and track defects; support root-cause analysis and collaborate with development teams for resolution. • Ensure full traceability between requirements, test cases, and results; support audits, reviews, and compliance with ASPICE, SOTIF and ISO 26262.

Key Responsibilities: • Lead V&V teams across software, hardware, and system domains. • Coordinate test activities with design, development, quality, and customer teams. • Creation of specifications and tests for the AI module, including integration test and system test • Define V&V milestones aligned with project timelines and product releases. • Support audits and assessments (ASPICE, ISO 26262, OEM-specific processes). • Develop and maintain test strategy, test plans, and test specifications. • Define validation environments (HiL, SiL, vehicle test, test benches, simulation). • Ensure traceability between requirements, test cases, and results. • Oversee execution of unit, integration, system, and acceptance testing. • Approve test procedures and ensure correct usage of test tools and equipment. • Review test results, analyze defects, and drive corrective actions. • Ensure proper documentation for compliance and release readiness. • Oversee the validation of AI and Vision models, evaluating their accuracy, robustness, and performance metrics. • Establish standardized validation workflows by developing automated scripts for vision-related testing and data analysis. • Provide actionable optimization recommendations to the development team based on empirical test results and performance analysis. • Ensure alignment with automotive standards such as: ASPICE (Automotive SPICE), ISO 26262 (Functional Safety), ISO 21448 (SOTIF), OEM-specific requirements (Toyota, Honda, VW, GM, etc.) • Build and lead a V&V team of 4 members, defining clear testing lifecycles, bug tracking standards, and reporting protocols for AI-driven products.

【Key Responsibilities】: • Develop and maintain the QA strategy for assigned SW projects in coordination with Quality Manager • Create, maintain and ensure the execution of the QA Plan for the project • Define, monitor and report quality KPIs at SW and ML model level • Prepare the quality status report highlighting non-conformities and quality risks to project management • Define escalation process to ensure identified non-conformities are addressed and resolved effectively • Perform internal gap analysis at SW and ML level to assess compliance with A-SPICE processes • Conduct work product reviews, audits and process compliance checks within the project • Collaborate with engineering and supply chain teams to resolve quality-related issues and implement corrective and preventive actions • Support project teams in preparing for internal and/or external ASPICE assessments for SW and ML • Facilitate lessons learned sessions and collaborate closely with software and ML engineering teams to implement A-SPICE process improvements and ensure alignment with functional safety standards • Ensure proper documentation and traceability across the development lifecycle, particularly for the SUP.1 process • Support the definition and refinement of the Product Development Process in alignment with organizational and project-specific quality requirements • Serve as the quality interface with Mandarin-speaking engineering teams and OEM counterparts, facilitating alignment on quality requirements and findings

SMT (PCBA) 1. Oversee QA operations, including inspections, supplier management, root cause analysis, and product reliability. 2. Develop and maintain quality management systems, including training programs. 3. Lead internal audits and external certifications (such as ISO, SPC...etc) for compliance with industry standards. 4. Drive quality improvement initiatives and manage customer complaints with preventive measures. 5. Engage clients through regular quality meetings and action plans. 6. Lead and develop the QA team, fostering accountability and continuous improvement. 7. Performs other related duties as assigned.

1.與顧問搭配,參與AI use case 的專案。 2.AI Agent 技術研究與應用開發。 3.串接既有AI技術，建置AI服務，並能掌握問題關鍵，提出可行的解決方案。 4.維運現有AI 專案系統,持續管理與優化。 ※依學經歷、工作年資敘薪

1. 協助專案用戶將業務需求轉化為可落地的 AI 解決方案。 2. 提供準確可靠的數據預測與解決方案，支持業務決策。 3. 應用統計分析、機器學習、深度學習、模擬與最佳化等方法，進行數據建模與分析。 4. 持續追蹤並評估最新 AI 技術，將尖端技術應用於實際營運場景中，解決痛點並提升效益。 5. 負責大型語言模型（LLM）的應用、訓練與優化，並熟悉雲端與地端部署環境。 1. Translate business requirements into practical AI solutions in collaboration with project stakeholders. 2. Deliver accurate and reliable data predictions and solutions to support decision-making. 3. Apply statistical analysis, machine learning, deep learning, simulation, and optimization methods for data modeling and analysis. 4. Stay up to date with the latest AI technologies and integrate cutting-edge methods into business processes to solve real-world challenges. 5. Develop, fine-tune, and deploy LLMs, with experience in both cloud-based and on-premises environments. ※依學經歷、工作年資敘薪

1.AI 模型應用、訓練與微調，熟悉雲端/地端與LLM 操作及應用。 2.了解使用大型語言模型進行訓練和微調。包括選擇合適的數據集、設計訓練流程，以及調整模型參數以達到最佳性能。資料科學家需具備使用框架如TensorFlow來實現這些過程的能力，並能夠針對特定任務優化LLM。 3.資料建模與分析，建立和訓練機器學習模型，選擇適當的算法進行數據分析，並從中提取有價值的見解。 4.持續監控與優化，監控模型性能，根據新數據進行調整和優化，以提高預測準確性和商業價值。 ※依學經歷、工作年資敘薪

【職務內容】 與仁寶AI Team建立與維護MLOps流程 ( ML + DevOps ) ，歡迎挑戰： 建置與維護 機器學習、深度學習、數據分析等 AI應用資料流工程 規劃設計以AI為核心的數據架構平台，例如AI K8S Platform建置與維護 與資料科學合作將模型上線應用並持續優化運算效能，不斷提升使用者體驗與產生經濟價值 ※依學經歷、工作年資敘薪

1.建構及維護商業智慧平台與數位化流程架構。 2.負責 BI 系統的導入，整合 BI 數據分析及維護管理。 3.進行 ETL 資料處理，並處理 Web 系統的整合與開發需求。 4.使用者需求訪談與系統分析，撰寫相關技術文件。 5.與跨功能團隊合作進行平台管理，解決技術問題，確保平台穩定運行。 6.協助研究 BI 平台新功能與技術趨勢，提出改進建議及專業報告。

1.設計、實施和管理企業基礎設施，並根據業務需求優化企業資源。 2.監控和排除系統環境中的問題，確保可用性、問題排除。 3.實施自動化工具以提高資源管理效率。 4.與開發和運維團隊協作，實現集成解決方案並持續改進系統架構。 5.管理平台需求規劃、架構設計、成本控管。 ※依學經歷、工作年資敘薪

1.設計、實施和管理企業基礎設施，並根據業務需求優化企業資源。 2.監控和排除系統環境中的問題，確保可用性、問題排除。 3.實施自動化工具以提高資源管理效率。 4.與開發和運維團隊協作，實現集成解決方案並持續改進系統架構。 ※依學經歷、工作年資敘薪