1. Fine-tune image quality for projects and communicate with customer
2. Production line calibration tool maintenance and development
3. 3A maintenance
愛德萬測試為全球半導體產業最大自動化測試設備(ATE) 供應商
Test program development and engineering support on V93000
須依據客戶與原廠需求 ,
協助對象包括 晶圓製造大廠,IC設計公司,設計服務公司 以及封裝測試公司
負責軟體 開發, 程式修改, 良率改善 , 周邊配件優化等工作,
負責客戶, 會依據實際需求安排.
基礎技能 , 需有 C or Java 等程式語言基礎,
工作內容:
1. 將AI ISP 影像處理模型部署至車用控制器平台(如 Qualcomm、NVIDIA、黑芝麻、MTK及各家NPU 等),確保AI模型在各類平台穩定運行。
2. 依據產品需求,評估模型在 GPU、CPU、NPU 等運算單元上的算力需求與資源佔用,進行性能分析與優化。
3. 與 AI ISP 演算法開發人員合作,完成模型移植、壓縮、加速與平台適配。
4. 針對不同平台環境進行測試與調優,確保模型滿足車用場景的即時性、穩定性與可靠性要求。
5. 參與車載系統軟硬體整合,協助解決模型部署過程中的技術問題。
6. 持續關注車用 AI SoC、NPU 與 ISP 平台的最新技術動態,熟悉各家平台與NPU使用方式,並提出相關改善與升級建議。
技能描述:
1. 資訊工程、電機電子工程、光電工程、影像處理等相關專業碩士及以上學歷。
2. 5年以上AI 模型開發或平台部署經驗。
3. 熟悉深度學習模型部署流程,具備 TensorRT、ONNX Runtime、TVM 或類似工具的經驗。
4. 具備 C/C++、Python 程式開發能力,了解嵌入式 Linux 環境。
Responsibilities:
1. Deploy AI ISP models onto automotive computing platforms (e.g., Qualcomm, NVIDIA, Black Sesame, MTK and NPU-based platforms), ensuring stable runtime performance.
2. Evaluate computational requirements and system resource usage (GPU, CPU, NPU, etc.) based on product needs, and perform resource consumption and performance optimization.
3. Collaborate with AI ISP algorithm developers to handle model porting, compression, acceleration, and platform adaptation.
4. Conduct testing and fine-tuning across different automotive platforms to guarantee real-time, stability, and reliability standards.
5. Support software-hardware integration for automotive systems and troubleshoot deployment-related technical issues.
6. Stay updated with the latest automotive AI SoC, NPU, and ISP platform technologies, providing insights for improvements and upgrades.
Skills Qualification and Experience:
1. Master's degree or above in Computer Science, Electrical/Electronic Engineering, Optoelectronics, Image Processing, or related fields.
2. Minimum of 5 years of experience in AI model development or platform deployment.
3. Familiar with deep learning model deployment workflows, with hands-on experience in tools such as TensorRT, ONNX Runtime, TVM, or similar frameworks.
4. 4Proficient in C/C++ and Python programming, with a solid understanding of embedded Linux environments.
1. Actively clean, process, and validate Data streams for ML model consumption. Contribute to the implementation of MLOps best practices (CI/CD) and risk mitigation strategies as guided by the engineering team.
2. Actively develop and implement Python scripts and small utilities for model features and basic algorithm testing. Ensure development practices align with model fairness and ethical guidelines.
3. Establish and track technical Key Performance Indicators (KPIs) to measure model effectiveness post-deployment. Document and report potential technical risks identified during implementation.
4. Create and maintain a single source of truth for all active Carrier/vendor technical requirements and specifications. Support the definition of project scope, timelines, and milestones.
5. Act as the central liaison between Engineers, Data Scientists, and Business stakeholders. Translate incoming high-level partner requests into clear, detailed, and actionable engineering specifications and tickets.
6. Provide regular, concise updates for stakeholders on project progress, key metrics, and any blockers.
7. Annual salary: 1000K NTD and above
8. Onsite Google Xindian Office