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【工作內容】 1. 負責影像處理(Python與C++)與資料處理。 2. 負責影像辨識軟體之分析、設計、程式撰寫、測試與修改，並控管進度。 3. 依照專案需求建立影像辨識模組與執行模型加速。 4. 邊緣硬

【職務情況說明】 Return Helper為跨境電商逆物流服務商， 自行開發倉儲逆物流/退貨平台系統提供台灣及全球賣家使用，讓退貨方式及倉儲管理更便利。 因應內部系統新功能開發、更新、維護等與日俱增

Jubo 正在招募 Machine Learning Engineer 機器學習工程師 加入其位於台灣新北市、針對台灣本地市場的產品研發團隊。對於真正合適的人選，這會是可以與高速成長、並擁有廣大國際連結的科技公司合作的獨一無二

如果你還會金融業抱持本土金融保守的想法，是時候該改變對金融業的看法了! 有種企圖想要把新創的氛圍帶入金融業，透過技術與數據說話。恭喜您! 與您抱持同樣想法，國內外名校，想法開放的

創充滿未知與挑戰的吸引力嗎？加入 LSC 和我們一起打造電動載具產業的霸業！ 【Responsibilities】 • 開發基於 Artificial Intelligence / Machine Learning / Deep Learning 交通領域之演算法應用 • 將模型演算法優化於 Cloud Computing，提供 API 服務 • 建構研發期之雲端模

主要職責: 智慧物流解決方案用AMR(Autonomous Mobile Robot) /AGV( Automated Guided Vehicle)自主導航相關演算法開發與維護 主要任務: A.開發智慧物流解決方案用AMR/AGV自主導航相關演算法 a.物件辨識(Object Recognition) b.同時定位與

- We are looking for experienced Machine Learning/Deep Learning engineers. - This is a technical role, and it requires a high willingness to learn state-of-the-art AI techniques and a skill to apply AI techniques to business applications/processes. - Participate in the engineering life-cycle, including writing production code, conducting code reviews and deploy machine learning solutions into production. - You’re not just looking for a job, you’re looking for an innovative

We are looking for a highly knowledgeable and enthusiastic machine learning engineer to help solve complex problems across a variety of audio processing projects. You will be both creating new solutions and evaluating existing machine learning (ML) processes, as well as performing statistical analysis to create and analyse large data sets. To ensure success as a machine learning engineer, you should be able to demonstrate solid data science knowledge and experience in a related ML role, as well

Giftpack Inc. 👉🏻 About Giftpack ( giftpack.ai/about ) Product: giftpack.ai | giftpack.io Giftpack is a gifting CRM that makes your relationship smarter with AI. Everything starts with a search for a heartfelt gift. From business to consumers; we are using technology to innovate the gifting industry. Since everyone has their preferences and personalities, we often spend so much time and effort and yet not be able to choose what our

主要負責內容為： 1. 建構各種Data Collection Pipelines 2. 建立自動及半自動化的Model Training Pipelines 3. 使用既有或引進新的工具來管理Datasets/Models/Configs 4. 部署ML Applications 5. 監控ML 服務以及協助除錯