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 Banqiao Office
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
【工作內容】
1. Architect, design, and develop AI agentic systems
【需求條件】
1.Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field.
2.Experience with RAG/MCP and backend code-generation
【加分條件】
1.Strong understanding of software data structures, algorithms, and proficiency in object oriented coding, preferably in C or C++. Exposure to AI/ML models, accelerators is a plus.
2.Familiarity with PyTorch, Tensorflow, ML models
3.Fluency in English
【工作地點】:台北/南投/WFH
This role might be the one you've been looking for if you are eager to get early access to cutting-edge AI and robotics technologies and be passionate about integrating hardware and software to apply AI in solving real-world challenges!
Join us if you're up for the challenge; also, providing an English CV would be a plus!
#Advanced communication skills in English is a must!
*About the Role:
We are looking for an engineer to build and deploy AI agents that can see and interact with the world through robotics systems. You will be working on everything from setting up hardware to coding intelligent agents for customer demonstrations.
*What You Will Do:
Hardware Setup & Deployment (20-30%)
•Install and configure Nvidia Jetson devices on robots
•Set up vision systems and troubleshoot hardware issues
•Ensure quick deployment for demos and exhibitions
*AI Agent Development (40-50%)
•Build AI agents using Large Language Models (LLMs)
•Work with AI frameworks like LangChain, CrewAI, or Hugging Face
•Connect AI agents to computer vision tools and robot controls
•Use platforms like Nvidia Agent Studio or Autogen for UI development
•Debug and optimize AI pipelines to meet project goals
*Computer Vision (10-20%)
•Work on object detection, image segmentation, or OCR systems
•Train and optimize vision models for robotics applications
•Develop new AI vision tools as needed
*Technical Requirements:
•Programming: Strong Python and PyTorch skills
•AI Frameworks: Experience with at least 1 LLM frameworks (LangChain, CrewAI, Nvidia NanoLLM/Agent Studio, Autogen, n8n, etc.)
•Computer Vision: 2+years experience in CV areas ex. object detection/segmentation
•Edge Computing: Experience with Nvidia Jetson devices
•Optimization: Knowledge of TensorRT, ONNX, or similar inference frameworks
•Development: Git, CI/CD, Linux/Windows environments
*Qualifications:
•Master's degree in Engineering, Computer Science, or related field
•2+ years of hands-on AI/Computer Vision experience
•Strong English communication skills is a must
•Ability to present technical solutions clearly
•Flexible and collaborative team player
若您渴望搶先接觸尖端AI與機器人技術,並希望透過融合硬體與軟體以實現運用AI技術來解決現實世界中會面臨到的問題的話,本職務或許是您正在尋覓的機會!
具體工作內容如下:
部屬與設置硬體設備(20-30%)
1.在機器人上安裝並配置 Nvidia Jetson
2.設置視覺系統並排除硬體設備相關問題
3.展場部屬設置
AI Agent 開發(40-50%)
1.使用大型語言模型(LLMs)構建 AI Agent
2.使用 LangChain、CrewAI 或 Hugging Face 等 AI 框架
3.將 AI Agent 與電腦視覺工具和機器人控制系統連接
4.使用 Nvidia Agent Studio 或 Autogen 等平台開發 UI
5.除錯並優化 AI 處理流程,以達成專案目標
電腦視覺(10-20%)
1.開發物體偵測、影像分割或光學字元辨識(OCR)系統
2.訓練並優化應用於機器人的視覺模型
3.根據需要開發新的 AI 視覺工具
技術要求:
1.程式設計:熟悉Python 和 PyTorch
2.AI 框架:至少熟悉一種 LLM 框架(如 LangChain、CrewAI、Nvidia NanoLLM/Agent Studio、Autogen、n8n 等)
3.電腦視覺:具備 2 年以上物體偵測或影像分割等相關經驗
4.邊緣運算:有使用 Nvidia Jetson 裝置的經驗
5.優化技術:熟悉TensorRT、ONNX 或類似推論框架
6.開發環境:熟悉Git、CI/CD、自如於 Linux/Windows 環境中工作
必要條件:
1.工程、計算機科學或相關領域之碩士學位
2.至少 2 年以上 AI / 電腦視覺實作經驗
3.具備良好的英語溝通能力(請準備英語簡歷)
4.能清楚表達技術解決方案
5.樂於協作的團隊精神
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. Understand types of LLMs (Text generation/Audio and speech recognition/Image generation)
2. Build up and deploy Open Models, Web API setup, permission management, and auditing
3. Embeddings function skill
4. Prompt engineering with context
5. Retrieval Augmented Generation (RAG)
6. Fine-tuned model
Reponsibility
• 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.
• 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.
• Establish and track technical Key Performance Indicators (KPIs) to measure model effectiveness post-deployment. Document and report potential technical risks identified during implementation.
• 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.
• 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.
• Provide regular, concise updates for stakeholders on project progress, key metrics, and any blockers.
Minimum Qualification
• Proficiency in programming Python, Database(SQL, Vector Database) and GCP(Google Cloud Platform).
• Familiar with AI Agent, Agentic AI, MCP, A2A, Context Engineering
• Experience with implementing machine learning algorithms in practice at scale.
• Good communication skills and a positive attitude to work with stakeholders.
• Proficient English speaking, reading, and writing ability.
• Minimum 7 years experience in an AI-related role.
Working location:
Banqiao or Xin-dian