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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

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

- 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

GLSoft 相信科技能夠創造更好的世界，我們正在尋找與我們有相同信念的夥伴加入我們的行列。 【 職務內容 】 1. 依據不同專案，與小組成員合作開發和維護客戶的長期專案需求 2. 根據產品需求文

和資料科學家/產品經理一起協作，了解公司需求以及提出解決方案 協助前瞻深度學習、機器學習算法的開發及優化 數據採集、標註前、後處理及算法開發與測試 蒐集及實作技術論文

想要擁有紮實的AI技術？ 想要跟上AI的最新趨勢？ 想要累積各產業的AI導入經驗？ 在工作中達成你的願望！ 工作內容： 人工智慧相關新技術研究與分享 企業內訓課程教材準備與授課 輔導與執行人

Superb technical, research and analytical capabilities with a demonstrated ability to get the right things done quickly and effectively. This person must be comfortable working with a team of top-notch developers and collaborating with our business team. We want people who innovate and love solving hard problems. Key responsibilities: - Fine tune and optimize LLM's - Building and maintaining data pipeline including data processing and data analytics - Developing and maintaining efficient and sca

【企業簡介】 希望人人一看見我們的logo，都會發出一聲「阿！」 為了提供讓世界驚豔的服務，我們致力於開發能夠帶來感動的技術，並創造出更便利且安全的社會。 發揮科技力量的最大極限、兼具先進技

工作職責： 負責推薦系統和廣告變現相關的數據支持，包括但不限於數據報表平台、數據分析平台等 負責數據的自動化分析處理工作，對巨量數據進行挖掘，產出數據分布規律、變化趨勢、關聯關系

合成系統。 2. 熟悉現在熱門資料庫、爬蟲、資料搜尋。 3. 熟悉TRANSFORMER、PROMPTING、INSTRUCT TUNING。 4. 熟悉Python、Pytorch、Keras，機器學習(machine learning)的各類算法，並有實際項目使用經驗。 5. 熟悉其中一門架構Bert、Attention、Transformer、 decoder ONLY、Vocoder、Unsupervised Learning、K means比較。 6