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NVIDIA’s Solution Architecture team is looking for a Data Science focused Solution Architect with expertise in Machine Learning (ML), Deep Learning (DL) and Data Science platforms. We work with the most exciting computing hardware and software, driving the latest breakthroughs in artificial intelligence. We need individuals who can enable customer productivity and develop lasting relationships with our technology partners, making NVIDIA an integral part of end-user solutions. We are looking for

📈穩定發展，打造全球資訊安全解決方案 🕵🏻領先業界，產業領頭羊 🦉與頂尖開發成員合作，增進開發實力 【職務內容】 通過 CloudWatch 構建 AWS 各種 Managed Services 的監控體系。 基於閾值或者 ML 對不同的 Metric 進行監控，通

分析(領域資料洞悉、特徵選擇、資料前處理等) 機器學習或其他相關演算法開發, 維運 機器學習模型改善以及效能調校 開發以及部署高度可擴展的機器學習模型 使用資料整合平台(如AirFlow) 建立 MLOps pipeline

的資料分析工作。 2. 開發和維護機器學習或其他相關演算法。 3. 改進機器學習模型並進行效能調校。 4. 開發並部署高度可擴展的機器學習模型。 5. 使用資料整合平台（例如AirFlow）建立MLOps流程。

析（領域資料洞悉、特徵選擇、資料前處理等） 機器學習或其他相關演算法開發, 維運 機器學習模型改善以及效能調校 開發以及部署高度可擴展的機器學習模型 使用資料整合平台（如 AirFlow）建立 MLOps 管線

▸ Participate in the entire development lifecycle of the MLOps platform ▸ Collaborate with Front-end developers to integrate user-facing elements with server side logic ▸ Collaborate with data engineers and data scientists to assist in the practical implementation of complex domain knowledgecould accelerate the ML dev cycle (MLOPs). ▸ Ability to adapt flexibly to various unforeseen and unfamiliar challenges ▸ Build reusable code and libraries for future use

1.進行大型語言模型(GPT等)的研究與應用導入。 2.開發與導入NLP技術於各部門業務場景，包括但不限於： (1)知識圖譜(Knowledge Graph) (2)向量資料庫(Vector DB) (3)多模態大語言模型 (MLLM) (4)應用：如輿論分析(Opinion analysis)等

Be responsible for managing our entire k8s-based infrastructure for MLOps.

detection/classification/recognition/tracking, behavior analysis, …) 和聲學處理 (Abnormal noise detection/classification, …) 3. 針對於不同的嵌入式系統的AI加速晶片(非GPU)進行模型壓縮與優化,以符合速度與準確度要求 4. 協助設計與建立MLOps流程與Data pipeline的介接工具

This position is for candidates with a career plan towards being an AI Full Stack Engineer. You will work with AI researchers in academia, implement algorithms, build computer vision services, and develop core ML pipelines. As a member of the AI team, you will work with worldwide fellow AI engineers, including engineers in our New York, India, and Taiwan branches. The goal of the AI team is to continuously optimize our core algorithms for extended-body estimation