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工作內容 Trading Strategy 開發、研究、維護、測試Trading Data Infra 設計與實作外部交易所介接 基本技術條件 (必備) 該職務投保單位為MaiCoin集團-恆阜股份有限公司至少三年以上工作經驗Golang 為主要需求 (若非 Golang，至少需具備 Java 或 C++ 等系統語言背景)主要在 backtest data warehouse 的基礎架構與 backtest 所需的 data engineering 能力資料庫與系統架構能力需熟悉 MySQL 或其他 RDBMS (backtesting pipeline 依賴大量資料處理與查詢效率)若具備 RabbitMQ、Kafka 或其他 message queue 經驗加分高效能系統經驗: 具備 high throughput / low latency 系統開發經驗者為佳交易相關基礎知識與加密貨幣交易經驗熟悉關聯式資料庫系統和 SQL需具備 Computer Science 或 EECS 等相關領域學士學位 次要技術條件 (有經驗者大加分) 熟悉股票交易或是其他金融相關經驗會 React 等前端開發工具加分熟悉資料處理工具 Python (numpy, pandas), R 等加分（但以精通 Golang 為主）Alpha Research 能力加分 福利與環境 Macbook + 27" 大螢幕隨時補充滿滿的零食與飲料不定期辦公室聚餐與教育訓練開放式管理風格與舒適工作環境便利交通位置，捷運站出口直達 出勤與休假 彈性上班時間，可在家工作員工一入職每年享有30日不扣薪事病假女性員工每年還有3日不扣薪生理假 薪資與津貼補助 保證百萬年薪年度健康促進補助NTD 30,000結婚補助NTD 12,000生育補助NTD 20,000 - NTD 50,000喪葬補助NTD 30,000團隊團建活動每季每人補助NTD 1,000員工推薦獎金員工三節禮券員工團體保險個人進修補助 人資或徵才聯絡方式 請將履歷夾帶於附件，寄信至 [email protected]，標題註明應徵 Algorithmic Trading Software Engineer， 我們將會與您聯絡。謝謝

🌟高流量🌟國際社群軟體開發商，致力於開發以地緣為主的社群平台，擁有將近五千萬人次下載量、數十億影片瀏覽次數，用戶遍及全球。比起關注遙遠的地點發生了什麼事，人對於發生在自己生活周遭的事物更有興趣。人們在這些熟悉的地方最有親切感與歸屬感，也因此關切在此發生的一切。我們藉由地緣結合短影片及區域話題群組探索生活周遭的新鮮事物，與所在地點有更深入的連結。🗣️新產品 AI Friend去年推出北美市場，與 ChatGPT 一問一答、整理資訊的模式不同，更像是朋友，能記住你的相關訊息，像是朋友的生日、最近的聊天內容等。該產品由一支20多人組成的AI團隊開發，已經研發多年。 如果你喜歡快節奏的工作模式，或者你希望擁有值得奮鬥的人生目標；想參與產品的快速成長，並期待在大流量的社群平台中獲得成就，歡迎聯繫我們。 工作簡述 我們正在尋找一位充滿熱情且技術熟練的AI工程師加入我們的團隊，負責設計、開發和實施人工智慧解決方案。你將與跨職能團隊合作，利用機器學習、深度學習和資料分析技術來解決複雜問題並推動產品創新。 工作內容 設計並開發AI模型，包括機器學習和深度學習演算法，用於解決業務需求。清理、預處理和分析大規模資料集，確保模型輸入資料的品質。將AI模型整合到現有系統或應用程式中，並優化其效能與可擴展性。與資料科學家、軟體工程師和產品經理合作，定義專案目標並交付成果。持續監控和改進已部署的AI系統，確保其準確性和可靠性。研究最新的AI技術和趨勢，並提出應用於公司產品的創新建議。撰寫清晰的技術文件，記錄模型開發過程和部署細節。 此職務的必要條件 至少2-3年AI、機器學習或相關領域的實務經驗。程式語言：熟練掌握Python，熟悉相關套件（如TensorFlow、PyTorch、Scikit-learn、Pandas等）。技術能力：深入理解機器學習演算法（例如回歸、分類、叢集）和深度學習框架（例如CNN、RNN、Transformer）。熟悉資料處理和特徵工程技術。有雲端平台經驗（如AWS、Google Cloud、Azure）者佳。問題解決能力：能夠獨立分析並解決技術挑戰。團隊合作：具備良好的溝通能力和跨部門協作經驗。學歷：電腦科學、資料科學、數學、工程或相關領域的學士學位（碩士或博士學位尤佳）。 加分條件： 有自然語言處理（NLP）、電腦視覺或強化學習的專案經驗。熟悉大數據工具（如Hadoop、Spark）或容器技術（如Docker、Kubernetes）。已發表過AI相關論文或擁有開源專案貢獻。 工作內容： 1. 資料分析(領域資料洞悉、特徵選擇、資料前處理等) 2. 機器學習或其他相關演算法開發, 維運 3. 機器學習模型改善以及效能調校 4. 開發以及部署高度可擴展的機器學習模型 5. 使用資料整合平台(如AirFlow) 建立 MLOps 管線

公司介紹｜About the Company 我們是一家深耕本土數十年的大型金融機構，現正積極推動AI數位轉型，從基礎數據整合到前線業務導入生成式AI應用，目標打造具預測性、個人化與自動化的智慧金融產品與服務。你將加入的是AI應用發展團隊的核心角色，參與企業級AI導入，並建構模型落地流程，是結合技術深度與產業影響力的理想舞台。 工作內容｜What You'll Do 主導並設計企業級AI應用場景與技術解決方案（如推薦系統、精準行銷、個人化服務） 開發與部署機器學習/深度學習/生成式AI模型，並負責模型上線、維運、效能監控 與內部跨部門協作，深入了解業務需求並轉化為可實作模型規格 領導大型AI導入專案，擔任內外部溝通窗口，控管進度與成效 持續關注並研究AI技術，如Gen AI、RAG、AI Agents、自動化機器學習等，並評估其在金融業務中的應用可能性 技術使用｜Tech Stack 語言與框架：Python, TensorFlow, PyTorch, Scikit-learn 資料處理：Numpy, Pandas 資料庫：Oracle, MS SQL Gen AI 技術：LangChain, RAG 架構, AI Agent 專案管理與溝通：跨部門需求對焦、POC設計與內部教育訓練

公司簡介 我們是一間專注於「生成式 AI 應用」的軟體新創，致力於打造能大幅降低人力成本、提升營運效率的智慧客服與自動化銷售解決方案。核心產品為基於 LLM GPT 的智能客服系統，已導入多家跨境電商、平台服務、消費品牌，並與全球頂尖 CRM、社交平台及 AI 工具公司合作。公司正快速成長中，誠摯邀請對 NLP 與 AI 商業應用有熱情的技術人才加入，一起打造世界級 AI 產品。 工作內容 你將成為 AI 團隊核心工程師，負責以下任務： 優化 Chatbot 的對話效能，特別是針對負向回饋自動優化模型與回應品質 訓練與調整 NLP 模型，如情感分析、意圖辨識、回應生成等深度學習應用 開發即時效能監控與預警系統，追蹤回應時間、滿意度、完成率等關鍵指標 分析大量對話紀錄，提出數據洞察，驅動產品優化方向 規劃與執行 A/B 測試，驗證不同模型與策略的效益 若有興趣，亦可參與 MLOps、雲端部署或強化學習相關項目發展 使用技術 語言與框架：Python、TensorFlow、PyTorch、SQL 雲端平台：AWS、GCP（擇一熟悉即可） 資料科學與分析：Pandas、Sklearn、統計分析與資料視覺化工具 開發流程：Git、unit testing、code review、CI/CD 產品場景包含多語系 NLP、客服任務導向對話、情緒分析與語意理解等

公司介紹 我們是一家深耕金融科技與資料智能應用的技術團隊，正積極將 大型語言模型導入高風險、高標準的實際業務場景。不同於單純模型實驗，這裡更關注 AI 是否「可靠、可驗證、可長期運作」。 團隊由資深工程與資料背景成員組成，文化務實、重視工程品質，並持續投入 AI Safety、模型評測與自動化流程，打造能被真正信任的生成式 AI 系統。 工作內容 設計並開發 LLM / RAG 系統的自動化評測工具與流程 建立模型多維度評分機制（Accuracy、Relevance、Faithfulness、Consistency） 將評測流程整合至 CI/CD（Jenkins / GitLab CI），確保模型版本品質穩定 與業務及資料團隊合作，建立高品質 Golden Dataset 與 Synthetic Data 執行 Prompt Injection、Jailbreak 等 LLM 安全與紅隊測試 分析失敗案例，協助定位 Retrieval 或 Generation 問題，驗證修復成效 使用的技術 Python、Pytest / unittest LLM / RAG Framework：LangChain、LlamaIndex、Semantic Kernel 資料分析：Pandas、NumPy、Visualization Tools 評測框架：RAGAS、TruLens、DeepEval、Promptfoo（加分） CI/CD、Git Docker / Kubernetes（加分）

Astera Labs (NASDAQ: ALAB) provides rack-scale AI infrastructure through purpose-built connectivity solutions. By collaborating with hyperscalers and ecosystem partners, Astera Labs enables organizations to unlock the full potential of modern AI. Astera Labs’ Intelligent Connectivity Platform integrates CXL®, Ethernet, NVLink, PCIe®, and UALink™ semiconductor-based technologies with the company’s COSMOS software suite to unify diverse components into cohesive, flexible systems that deliver end-to-end scale-up, and scale-out connectivity. The company’s custom connectivity solutions business complements its standards-based portfolio, enabling customers to deploy tailored architectures to meet their unique infrastructure requirements. Discover more at www.asteralabs.com.Job Description Astera labs is seeking a skilled and motivated Data Scientist. This individual will play a pivotal role in identifying key data points for collection, developing strategies to accumulate data and deriving actionable insights an anomaly based on a solid foundation of relevant know-how. Also, will also be responsible for creating, testing, and deploying scripts and methods for data collection and analysis to support decision-making. The Engineer will collaborate with cross-functional teams to identify critical data sources to determine the most effective data collection strategies, will develop automated and scalable data collection pipelines, will ensure data quality, integrity, and consistency across all sources and may use AI techniques to refine the results toward failures predictions. Basic Qualifications Bachelor’s degree in computer science, Data Science, Engineering, Mathematics, or a related field. Advanced degrees in data science or Machine learning / AI - Advance. Proficiency in programming languages such as Python, R, or MATLAB. Strong understanding of data manipulation and analysis tools (e.g., Pandas, NumPy, SQL). Understanding of high speed interfaces such as Ethernet, PCI-E , WiFi. Experience with data visualization tools such as Tableau, Matplotlib, Graphana. Strong analytical and critical-thinking skills to identify patterns and outliers. Customer-obsession, Think and act with the customer in mind! Goal-driven, Self-motivated, be able to work independently and with teams with people around the globe. Entrepreneurial, open-minded behavior and can-do attitude. Required Experience Experience with data manipulation and analysis tools (e.g., Pandas, NumPy, SQL). Machine learning and AI techniques and frameworks (e.g., TensorFlow, Scikit-learn). Proven ability to manage multiple tasks and meet deadlines. Preferred Experience Embedded Firmware development with C-language, scripting with Python or other equivalent programming languages. Master’s degree in a relevant field. Experience with cloud platforms (e.g., AWS, Azure, GCP) for data storage and processing. Familiarity with big data technologies (e.g., Hadoop, Spark). Knowledge of engineering design tools and processes. We know that creativity and innovation happen more often when teams include diverse ideas, backgrounds, and experiences, and we actively encourage everyone with relevant experience to apply, including people of color, LGBTQ+ and non-binary people, veterans, parents, and individuals with disabilities.

Google welcomes people with disabilities.Minimum qualifications: Bachelor's degree or equivalent practical experience. 5 years of experience using Python (Pandas, NumPy) or Java to develop data processing tools or automation scripts. Experience in managing data workflows using tools like Airflow, dbt, or Prefect. Experience in building and querying data within BigQuery, Snowflake, or Redshift environments. Experience in developing operational dashboards using Looker, Tableau, or Power BI. Preferred qualifications: Experience working with semiconductor manufacturing data or large-scale industrial datasets. Ability to manage complex data exchanges and integration workflows with external foundry or assembly partners. Ability to identify manufacturing anomalies and to explain architectures to non-technical stakeholders. About the jobA problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Program Manager at Google, you’ll lead complex, multi-disciplinary projects from start to finish — working with stakeholders to plan requirements, manage project schedules, identify risks, and communicate clearly with cross-functional partners across the company. Your projects will often span offices, time zones, and hemispheres. It's your job to coordinate the players and keep them up to date on progress and deadlines. As a Machine Learning Data and Analytics Engineer, you will be the architect of manufacturing intelligence. You will design, build, and maintain the data infrastructure that transforms fragmented information from the global partners into a cohesive, high-performance data ecosystem. Your work will directly enable the operations team to monitor production health, optimize yields, and make data-driven decisions in real-time.The Data Center team designs and operates some of the most sophisticated electrical and HVAC systems in the world. We are an upbeat, creative, team-oriented group of engineers committed to building and operating powerful data centers.Responsibilities Design and deploy pipelines to manage high-volume manufacturing data, including wafer maps, test results, and quality reports. Build automated tools to clean and normalize disparate data formats from foundry and assembly partners, ensuring a single source of truth. Create and maintain intuitive visualizations and dashboards to monitor the Key Performance Indicator (KPIs) and production health metrics. Develop and optimize data schemas that support high-speed ingestion and investigative querying for real-time decision-making. Partner with Operations and Engineering teams to translate business requirements into technical solutions while ensuring platform reliability and performance. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor's degree in Computer Science, Engineering, Mathematics, Operations Research, or a related quantitative field. 2 years of experience in developing and deploying Machine Learning models or AI-driven applications. Experience with agent-based modeling, predictive modeling, or deep learning architectures. Experience with prompt engineering. Preferred qualifications: Experience in Python and standard data science libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow/PyTorch). Experience putting data science principles into practice, data quality assessment, statistical modeling, feature engineering, and data visualization. Experience with frameworks like LangChain or LlamaIndex, to build advanced, multi-step agents. Experience in using vector and graph databases to power Retrieval-Augmented Generation (RAG) in supply chain processes and systems. Experience working with cloud computing platforms (e.g., Cloud Computing Platform, Google Cloud Platform) and developing solutions that interact with large-scale data warehouses and databases (SQL, NoSQL). Familiarity with optimization techniques (linear programming, heuristic search) and simulation modeling. About the jobA problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Design, build, and prototype AI agents focused on optimizing key supply chain functions for cloud compute infrastructure (e.g., forecasting, capacity planning, demand sensing, component procurement, logistics, and reverse logistics). Iterate on ideas, conducting rapid A/B testing and proof-of-concept experiments to validate the technical feasibility and business impact of agent-based solutions. Create comprehensive documentation, including technical specifications, model architecture, and model maintenance procedures to ensure a seamless and efficient transition of successful prototypes to production engineering teams. Run regression tests in production to validate model outcomes. Partner closely with Supply Chain Operations, Architects, Finance, and Engineering teams to define requirements, gather feedback, and ensure prototypes align with strategic business objectives and drive user adoption in production. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google welcomes people with disabilities.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New Taipei, Banqiao District, New Taipei City, Taiwan; Zhubei, Zhubei City, Hsinchu County, Taiwan.Minimum qualifications: Bachelor’s degree or equivalent practical experience. 5 years of experience in program management. 5 years of experience working with data in a data engineer, or data scientist role. Experience in analyzing data using programming languages and analysis tools (e.g., Python, R, JMP). Preferred qualifications: Master’s degree in Electrical Engineering, Computer Science, or a related field. 10 years of experience as a data engineer in related semiconductor companies. Experience with silicon testing and yield methodologies, test data formats (ex: STDF), and common silicon analysis techniques. Experience with Colab or Jupyter Notebooks, with an understanding of SQL for data validation and querying. Experience gathering and documenting analysis requirements from stakeholders, translating them into actionable specifications, and soliciting feedback for continuous improvement. Excellent data analysis and visualization skills using Python, Pandas, and libraries like Matplotlib, or Plotly. About the jobAs a Process and Yield Engineer for Custom Silicon you will join the team responsible for High volume Custom Silicon Manufacturing to build a data visualization system for semiconductor production including building customized scripts and enabling big data query. Yield and process improvement and scrap optimization, manufacturing performance, quality and excursion management and prevention, value engineering, change control management, new production site qualifications for alternate sourcing and business continuity. HVM capacity readiness, cycle time optimization and more!Googles mission is to organize the worlds information and make it universally accessible and useful. Our Devices Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our users interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices Services team is making peoples lives better through technology.Responsibilities Lead the end-to-end development for custom data tools and dashboards for custom silicon engineers, from requirements gathering and prioritization through prototyping and deployment. Improve data analytic efficiency utilizing internal AI workflow or create agentic AI tools. Develop and manage processes and automated systems for monitoring silicon data quality from Contract Manufacturers (CMs) and internal sources, ensuring data integrity for engineering analyses. Act as the key technical liaison between custom silicon and data platform teams, advocate the creation and iterative improvement of custom analytical tools and dashboards driven by user feedback. Leverage deep knowledge of the custom silicon data ecosystem (including data sources, pipelines, database structures, data integrity, etc.) to manage projects, troubleshoot issues, and lead the technical integration of custom dashboards and investigative features into a data platform. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform. WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers and portfolio managers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people. The Role We are seeking an exceptional senior-level Python engineer to join a small team working on complex data pipelines, AI/ML systems, and cutting-edge software solutions. This role will be responsible for managing technical objectives, providing technical leadership, and maintaining a hands-on approach to development. The ideal candidate will work closely across teams within WorldQuant as part of our business-facing technology organization. A successful candidate will possess deep expertise in Python development, data engineering, software architecture, and design principles. They should be able to mentor junior team members, conduct code reviews, and drive architectural decisions. Experience with AI and large language models (LLMs) is highly desirable. What You'll Bring Master's degree or higher in Computer Science, Engineering, or a related technical field from a top-tier institution. 7+ years of experience as a Python developer, with a strong focus on data engineering and AI/ML systems. Expert-level knowledge of Python and its ecosystem, including experience with data processing libraries like Pandas, NumPy, and PySpark. Proficiency in designing and implementing scalable, maintainable, and efficient data pipelines. Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes). Expertise in version control systems (Git), CI/CD practices, and agile methodologies. Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders. Experience in the finance industry is a plus but not required. Experience with AI/ML frameworks such as PyTorch, or scikit-learn, LLM, agents or systems of agents is a significant plus. #LI-DN1By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction. Copyright © 2025 WorldQuant, LLC. All Rights Reserved.WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.