Cake 求人検索

Dcard 是在年輕族群有極高滲透率與影響力的社群平台。我們致力於打造一個讓每個人都可以放心分享自己故事的地方，讓平凡人分享不平凡故事的新世代社群服務。面對快速變化的社群生態，我們期待更多優秀的人才加入 Dcard。為了達成這個目標，我們需要 Senior Machine Learning Engineer (Ads) 加入我們， 你將有機會可以接觸到⼤量⽤戶產生的實際資料，加入這個熱愛挑戰的團隊，一起打造被千萬人喜愛與使用的產品！ 你將在團隊參與⋯ 參與 Dcard 機器學習相關產品的開發以及演進，可能會碰觸到演算法開發、模型訓練、Feature pipeline 設計以及維護服務的正常運作。與其他 Data Component 的開發者合作，一起建置 Dcard 機器學習相關系統。從大量使用者數據中分析、挖掘洞察以迭代演算法優化。設計並進行 A/B 測試實驗，驗證演算法的成效。

公司介紹 本職缺來自全球用戶突破億級的加密科技平台，團隊推動 AI、區塊鏈、Web3 應用整合，致力打造下一代數位生活體驗。公司設有創新實驗室（Innovation Lab），專注於 Generative AI 應用與技術研發，支持全遠端工作與跨國團隊合作。台灣已設立據點，歡迎本地優秀人才加入！ AI / Machine Learning Engineer (with a focus on Generative AI) Job Summary: We are seeking a highly skilled and motivated AI/Machine Learning Engineer to join our innovative team. The ideal candidate will have a strong background in developing predictive models and a deep passion for the rapidly evolving field of Generative AI. You will be responsible for the end-to-end development of AI solutions, from data processing to model deployment, and will play a key role in leveraging cutting-edge AI technologies to solve real-world challenges across various domains. Responsibilities: Develop and maintain robust data pipelines to process and analyze large volumes of information, preparing high-quality datasets for model training. Build and deploy predictive models and machine-learning algorithms to discover trends, patterns, and actionable insights from data. Design, develop, and implement generative AI models to address complex challenges in areas such as natural language processing, image synthesis, and video/voice generation. Conduct ongoing research on emerging generative AI techniques, algorithms, and best practices to ensure our solutions remain state-of-the-art. Collaborate effectively with cross-functional teams, including product managers, software engineers, and domain experts, to design and deploy integrated AI solutions.

【團隊介紹】 我們是一個充滿熱情與創意的團隊，致力於結合科技與數據驅動保險業的創新變革。在這裡，你將與專業的技術與商業團隊協作，打造下一代智能解決方案，推動產險的數位轉型與智能化發展。 我們相信，未來的保險不僅僅是理賠和風險分攤，更是結合數據與AI技術實現全方位的風險預測與預防。 無論是車險理賠自動化、自然災害風險評估，還是風險預防方案，我們不僅在傳統產險領域引入前沿技術，也正在探索保險科技的無限可能。 如果你熱愛結合商業與技術，並希望將創意和洞察力轉化為可落地的AI解決方案，這裡將是你大展身手的最佳舞台！加入我們，與數據和科技共同塑造保險的未來！👀更多關於我們做的數據服務，期待您的加入，運用數據專案管理與技術整合能力，推動 AI 轉型與數據生態建構，讓數據創造最大價值！1. 九成跨域人才！國泰產險多元跨域、探索共融 打造數位數據轉型創新基地🔗https://www.bnext.com.tw/article/81887/cathay_ddt_2025012. 國泰產險推業界首創「CarTech智能車險加值服務」，數據驅動助法人車隊落實損害防阻🔗https://www.bnext.com.tw/article/81313/cathay-ins2024113. 國泰產險數位轉型新里程！AI與數據驅動加速全險種理賠、提升風控更有效阻詐2,300萬🔗https://www.bnext.com.tw/article/81460/samrtclaim_2024

Established in 1987 and headquartered in Taiwan, TSMC pioneered the pure-play foundry business model with an exclusive focus on manufacturing its customers’ products. As of 2024, TSMC serves more than 500 customers and manufactures over 11,000 products for high-performance computing, smartphones, the Internet of Things (IoT), automotive, and digital consumer electronics. It is the world’s largest provider of logic ICs, with an annual capacity of 16 million 12-inch equivalent wafers. TSMC operates fabs in Taiwan as well as manufacturing subsidiaries in Washington State, Japan and China, and the Company began construction on a specialty technology fab in Dresden, Germany, in 2024. In Arizona, TSMC is building three fabs, with the first starting 4nm production in 2025, the second by 2028, and the third by the end of the decade.Advanced Quality System Development (AQSD) is part of TSMC's Intelligent Manufacturing Center (IMC), responsible for three main directions: Use statistical methods and conditional monitoring to inspect fab control charts, providing early warning of abnormal product yields; offer a fab defense system settings comparison platform to check that machines meet the internal control anomaly conditions set by the engineering department.Develop online fab analysis platforms through Big Data, Machine Learning, and Deep Learning techniques for online yield/defect analysis to ensure the quality of wafers produced in the fab.Develop systems and provide logical operations to control and implement escape mechanisms for material batch changes, measurement stages, and inspection stages, ensuring quality and optimizing product sampling rules. Responsibilities: Apply machine learning/optimization algorithm to build up models for optimizing semiconductor production.Develop analysis and optimization methods to enhance product quality, increase tool productivity and improve people productivity.Design, develop and test prediction models with real applications in manufacturing.Build a flexible framework to speed up the development process of AI models, with a focus on Large Language Models (LLMs) serving.Turn exciting AI prototypes/ideas into products, leveraging LLMs and other advanced AI technologies.Develop next-generation AI backend systems related to large-scale real-time data access, collection, analytics and monitoring.Establish and maintain MLops processes and tools, including model deployment, monitoring, and automation.Continuously improve the quality of AI production systems, particularly those utilizing LLMs.

Established in 1987 and headquartered in Taiwan, TSMC pioneered the pure-play foundry business model with an exclusive focus on manufacturing its customers’ products. As of 2024, TSMC serves more than 500 customers and manufactures over 11,000 products for high-performance computing, smartphones, the Internet of Things (IoT), automotive, and digital consumer electronics. It is the world’s largest provider of logic ICs, with an annual capacity of 16 million 12-inch equivalent wafers. TSMC operates fabs in Taiwan as well as manufacturing subsidiaries in Washington State, Japan and China, and the Company began construction on a specialty technology fab in Dresden, Germany, in 2024. In Arizona, TSMC is building three fabs, with the first starting 4nm production in 2025, the second by 2028, and the third by the end of the decade. AQSD (Advanced Quality System Development) is part of TSMC's Intelligent Manufacturing Center (IMC), responsible for three main directions: Use statistical methods and conditional monitoring to inspect fab control charts, providing early warning of abnormal product yields; offer a fab defense system settings comparison platform to check that machines meet the internal control anomaly conditions set by the engineering department.Develop online fab analysis platforms through Big Data, Machine Learning, and Deep Learning techniques for online yield/defect analysis to ensure the quality of wafers produced in the fab.Develop systems and provide logical operations to control and implement escape mechanisms for material batch changes, measurement stages, and inspection stages, ensuring quality and optimizing product sampling rules. Responsibilities AQSD Engineer for Quality system development using C#, python, Delphi, Web programming like java script, react/angular/Vue framework, etc.A highly motivated individual with a background and capability to design a system to support quality management and solve Fab problems.Working with a team which may include integration, module, quality team to achieve productivity, efficiency and quality excellence.Analysis and optimize Fab quality management and delivery good solution.Be responsible for sustaining ownership such as system operations.

We are looking for a savvy ML Engineer intern. The hire will join the development and optimization of our AI applications. They're being built on top of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and AI Agents. As an intern you will have the rare chance to turn the newest research papers into products that touch 20 M+ users in Taiwan. Responsibilities Apply state-of-the-art machine learning, deep learning and generative-AI techniques to improve the quality of LINE TODAY, Stickers, Shopping, VOOM and future services.Prototype LLM-powered agents (tool-calling, multi-step reasoning, autonomous task execution) that automate internal workflows and elevate user experience.Translate business questions into data pipelines: collect logs, craft features, build and evaluate models (regression, classification, recommendation, time-series forecasting, anomaly detection, uplift modelling).Run fast experiments—offline metrics, A/B tests—and ship models to production with MLOps best practices (MLflow/Kubeflow, CI/CD, monitoring, drift detection).Keep the team on the cutting edge: read the latest NeurIPS / ACL / CVPR papers, hack up proof-of-concepts, present insights and drive “paper-to-prod” sprints. Working Period: 2026/03-2027/02, at least 3 days a week

Established in 1987 and headquartered in Taiwan, TSMC pioneered the pure-play foundry business model with an exclusive focus on manufacturing its customers’ products. As of 2024, TSMC serves more than 500 customers and manufactures over 11,000 products for high-performance computing, smartphones, the Internet of Things (IoT), automotive, and digital consumer electronics. It is the world’s largest provider of logic ICs, with an annual capacity of 16 million 12-inch equivalent wafers. TSMC operates fabs in Taiwan as well as manufacturing subsidiaries in Washington State, Japan and China, and the Company began construction on a specialty technology fab in Dresden, Germany, in 2024. In Arizona, TSMC is building three fabs, with the first starting 4nm production in 2025, the second by 2028, and the third by the end of the decade. The AI4BI team serves as the central intelligence hub within the Corporate Planning Organization (CPO). Our mission is to empower business users with AI-driven solutions that enhance customer satisfaction and streamline operational efficiency. We work closely with stakeholders who blend deep domain expertise in areas like demand and capacity planning with strong analytical capabilities.As an AI Engineer in the Product Innovation department, you will collaborate closely with product managers, designers, and internal business users to prototype and integrate new features into products. You are self-motivated and naturally curious, driven to innovate and deliver impactful results. Responsibilities: 1. Drive Innovation and Impact: Pioneer novel AI/ML solutions from initial concept to functional prototype. Shape the future of our internal product with your discoveries.2. Collaborate with Business Users: Work closely with internal stakeholders to understand needs and translate them into actionable AI-driven solutions that create measurable value.3. Apply Smart AI Techniques: Choose and implement the appropriate methods—classic machine learning, deep learning, or generative AI—to effectively solve diverse problems.4. Partner Across Teams and Geographies: Collaborate with cross-functional, global teams including AI researchers, engineers, and domain experts to integrate AI into production systems.5. Share Knowledge and Stay Current: Communicate insights through data storytelling, mentor colleagues, and proactively adopt emerging AI/ML trends to continuously improve solutions.

Minimum qualifications: Bachelor's degree or equivalent practical experience. 6 years of experience with cloud native architecture in a customer-facing or support role. Experience in pre-sales and consulting, delivering technical presentations, and leading discovery and planning sessions with customers with defined scope and success criteria. Experience with frameworks for deep learning (e.g., PyTorch, TensorFlow, Jax, Ray, etc.) and using machine learning APIs. Preferred qualifications: Experience in building and deploying data and Machine Learning (ML) pipelines with a focus on automation. Experience with prompt tuning and delivering successful prototypes. Experience in building machine learning solutions and leveraging specific machine learning architectures (e.g., deep learning, LSTM, convolutional networks, etc.). Experience working in technology sales within South East Asia region. Experience in understanding customer’s existing software workloads, with the ability to define a technical migration roadmap to the cloud reflecting specific customer needs. Ability to communicate in Bahasa Indonesia fluently to support client relationships in the region. About the jobThe Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners. As a Customer Engineer, you will partner with technical business teams as a subject matter expert in Artificial Intelligence and Machine Learning (AI/ML) to differentiate Google Cloud to the customers. You will help prospective and existing customers and partners understand the power of Google Cloud, develop creative cloud solutions and architectures to solve their business tests, engage in proofs-of-concepts, and troubleshoot any technical questions and roadblocks. You will engage with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud. You will partner with internal engineering stakeholders to improve products and build solutions, optimize for results when in production, and identify innovative ways to multiply the impact of the team as a whole.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge 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 Work with the team to identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers. Share in-depth AI/ML expertise to support the technical relationship with customers, including technology advocacy, supporting bid responses, product and solution briefings, proof-of-concept work, and partner directly with product management to prioritize solutions impacting customer adoption to Google Cloud. Work directly with Google Cloud products to demonstrate and prototype integrations in customer and partner environments. Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to successfully implement a complete solution on Google Cloud. Travel to customer sites, conferences, and other related events and act as a public advocate for Google Cloud. 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.

1. 開發生成式AI相關應用2.協助資料收集、清理與處理文本/音檔資料]3. 參與 LLM 與語音模型(如 Whisper) 的微調與優化4. 協助開發與測試模型、提升文本生成與語音辨識的準確性與相關性5. 研究並嘗試不同的模型整合與優化方法6.其他主管交辦事項*必要技能: 1. 熟悉機器學習、自然語言處理(NLP)、向量資料庫或 RAG 技術有基礎理解2. 熟悉 Python，並了解基本的機器學習/深度學習工具(如 PyTorch、TensorFlow、scikit-learn任一皆可)3. 對LLM或語音AI模型有興趣，願意投入研究與實作，具備良好學習能力及問題解決能力

Google welcomes people with disabilities.Minimum qualifications: Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience. 4 years of experience in business requirements analysis and business stakeholder management. 4 years of experience in a customer-facing role such as technology consultant, technical architect, enterprise architect, technical business engineer, or solutions architect. Experience with frameworks for deep learning (e.g., PyTorch, Tensorflow, Jax, Ray, etc.), AI accelerators (e.g., Tensor Processing Units (TPUs), Graphics Processing Units (GPUs)), model architectures (e.g., encoders, decoders, transformers), and using machine learning Application programming interfaces (APIs). Ability to communicate in Japanese fluently to support client relationship management in this region. Preferred qualifications: Master's degree in Computer Science, Statistics, or a related technical field. Experience in using natural language processing or natural language related to machine learning projects. Experience in building machine learning solutions and leveraging machine learning architectures (e.g., deep learning, Load Shedding and Traffic Management (LSTM), convolutional networks). Ability to learn, understand, and work with new emerging technologies, methodologies, and solutions in the cloud or IT technology environment. About the jobWhen leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products. In this role, you will partner with technical business teams as a data analytics subject matter expert to differentiate Google Cloud to the customers. You will help prospective and existing customers and partners to understand the power of Google Cloud, develop cloud solutions and architectures to solve their business tests, engage in proofs of concepts, and troubleshoot any technical questions and roadblocks related to database migrations, data back-end and all aspects of the data lifecycle. You will engage with customers to understand their business and technical requirements, and present solutions on Google Cloud.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge 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 Share Artificial Intelligence (AI/ML) expertise to support the technical relationship with customers, including technology advocacy, supporting bid responses, product and solution briefings, proof-of-concept work, and partnering with product management to prioritize solutions impacting customer adoption to Google Cloud. Be responsible for go-to-market strategy from a technical perspective. Unlock product gap for adoption working with the Product Engineering team. Work with the team to identify and qualify business opportunities, understand customer technical issues, and develop the strategy to resolve technical blockers. 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.