Cake 找工作

建構與優化機器學習模型: 運用多維度運動數據（如賽事數據、球員表現），開發球員薪資計算、表現預測等核心模型，並持續進行優化。 支援產品與行銷決策: 深入分析用戶行為與市場趨勢，提供數據洞察，協助產品團隊優化功能、支援行銷團隊制定精準策略。 整合生成式 AI 應用: 導入並開發生成式 AI 功能，例如自動化產出運動新聞與球員動態，豐富產品內容。 提升內部數據工作流程效率: 運用 AI 技術優化資料處理、分析與建模的流程，提升團隊整體開發效率。

We are seeking a Senior Software Engineer to be the technical heartbeat of our GenAI security capabilities. In this role, you sit at the exciting intersection of Research and Product, turning breakthrough experiments into scalable, production-grade software. You won’t just be implementing features; you’ll be designing the sophisticated tooling and AI Agent architectures that make the Vulcan Platform unique. We offer a playground for builders who want to solve unsolved problems, master advanced prompt engineering, and work alongside a world-class team. Come build the shield for the AI era and expand your technical horizons Learn more about us 👉 Vulcan product: https://vulcanlab.ai/Vulcan LinkedIn:https://www.linkedin.com/company/vulcanlab-ai/AIFT group:https://aift.io/ - How to apply Please apply with English CVthroughhttps://job-boards.greenhouse.io/aift/jobs/5744136004 Thank you. - What you'll do 1. Core Application Platform Development (Full Stack) Vulcan Platform: Partner with Product and Design to build intuitive frontend interfaces (React, Next.js) for dashboards, configuration consoles, and visualization tools. Backend Services APIs:Develop and maintain the essential APIs (FastAPI/Python) and microservices that power the Vulcan platform. Architect robust task execution systems using Message Queues (Celery, RabbitMQ) to handle long-running asynchronous AI inference tasks. Internal Tooling Ecosystem: Build frontend and backend tools that accelerate internal teams (Project, ML/AI), including configuration panels, data visualization pipelines, and evaluation interfaces. Guardrails Security Features: Implement backend services for AI guardrails (content moderation, prompt filtering) and automated adversarial testing pipelines. 2. GenAI Agent Logic Engineering Prompt Engineering as Code: Treat prompts as software logic. Lead the design and implementation of AI Agent behaviors, optimizing responses through structured Prompt Engineering techniques. Agent Workflow Design: Orchestrate complex, multi-step LLM workflows where the "application logic" involves chaining model interactions effectively. Response Handling: Design robust parsing and validation mechanisms to ensure raw model outputs are converted into structured, usable application data. -

Our Product Vulcan is a cybersecurity solution specifically designed for GenAI, offering two core services: Red Team (vulnerability assessment) and Blue Team (real-time defense). It ensures GenAI compliance, cybersecurity robustness, and operational integrity. Since its official launch in 2024, Vulcan has been recognized by the international standard-setting organization OWASP as a certified vendor for LLM GenAI security testing and assessment. It is one of the few solutions capable of supporting multiple Asian languages (Traditional Chinese, Simplified Chinese, Japanese, Korean, Thai) and Standard Arabic.Learn more about us 👉 Vulcan product: https://vulcanlab.ai/Vulcan LinkedIn: https://www.linkedin.com/company/vulcanlab-ai/AIFT group: https://aift.io/Tech Blog: https://medium.com/onedegree-tech-blogAbout the roleWe are looking for a talented Machine Learning Engineer to join our Product Core Engineering team. You will be responsible for building and optimizing machine learning workflows that directly power our AI-driven products. This role focuses on the full lifecycle of model development — from training and fine-tuning to deployment and monitoring — ensuring robust and efficient ML systems at scale. Why Join Us?Product Impact: Your work will be directly embedded in our core AI products, shaping user experience and product capabilities.Engineering Excellence: Be part of a team that values high-quality engineering, reproducibility, and scalability.Innovation: Opportunity to experiment with cutting-edge ML and GenAI technologies in production settings.Collaboration: Work alongside backend, platform, and product teams in a highly collaborative environment.Competitive Package: Receive attractive compensation and benefits aligned with your skills and performance. Key Responsibilities Model Development: Design and implement training processes for machine learning classifiers and generative models.Fine-tuning Prompting: Adapt pre-trained models to specific product needs through fine-tuning, prompt engineering, and parameter optimization.Hyperparameter Management: Configure and tune hyperparameters to balance accuracy, robustness, and performance.Pipeline Engineering: Build scalable training and evaluation pipelines to support continuous experimentation.Integration: Collaborate with backend and product engineers to deploy models into production systems.Monitoring Maintenance: Establish monitoring metrics and retraining strategies to maintain model performance in dynamic environments. -

Vulcan’s mission is to keep Generative AI safe, secure, and compliant for organizations worldwide. As a Frontend Software Engineer, you’ll build intuitive, high-performance user interfaces for products like Vulcan Protect (real-time monitoring dashboards) and Vulcan Attack (security insights and controls for automated vulnerability assessments). Working with a modern frontend-focused tech stack, you’ll collaborate closely with AI security experts and backend engineers to translate complex security, compliance, and reliability challenges into clear, actionable user experiences. In this dynamic, mission-driven environment, you’ll write high-quality, maintainable frontend code, contribute to UI/UX and architectural design reviews, and help shape products that make GenAI adoption safer and smarter. We value people who are creative, speak up with their ideas, take ownership as a team player, actively engage in discussions, are eager to learn, and are easy to collaborate with. Learn more about us 👉 Vulcan product: https://vulcanlab.ai/Vulcan LinkedIn:https://www.linkedin.com/company/vulcanlab-ai/AIFT group:https://aift.io/ - How to apply Please apply with English CVthroughhttps://job-boards.greenhouse.io/aift/jobs/5744133004Thank you. - What you'll do Focus primarily on building and maintaining features for Vulcan’s products, with an emphasis on frontend development using TypeScript, React, Next.js, React Query, Tailwind CSS, etc. Utilize additional tools and technologies as needed with GitLab CI, Docker, shell scripting, etc. Write clean, efficient, and testable code, primarily for frontend systems, with some backend contributions. Collaborate with team members during design and code reviews to build scalable, high-quality solutions, with a focus on frontend architecture. Troubleshoot and resolve technical issues by analyzing logs, system performance, and user feedback. Build and maintain internal tools to support project teams. Contribute to documentation and keep it current as our products and team grow, with an emphasis on frontend-related updates. -

參與生成式AI、判別式AI和AI自動化等領域的專案開發，包括但不限於： 自然語言處理應用（例如文案生成、內容摘要）AI代理系統（例如自然語言處理、對話管理、任務執行等）機器學習模型開發與整合RPA和API自動化解決方案與團隊成員及其他部門協作，參與技術研討與方案設計，推動AI應用落地根據業務需求設計與實作大型語言模型（LLM）的微調與優化，以適應特定業務領域的需求參與AI模型的效能測試、除錯、效能優化和部署，確保模型在生產環境中穩定高效運行開發及整合各類API介面，實現AI系統與異質系統間無縫整合協助制定AI應用的最佳實踐和標準，推動公司內部的AI知識分享和培訓持續關注AI領域的最新發展，評估新技術的應用潛力，並提出創新的解決方案負責內部AI應用文化的建立，提升AI數位賦能

國內最大化妝品使用心得及排行榜綜合網站@cosme Taiwan(前身UrCosme,2004年創建)在台營運20年，為國內消費者找尋化妝品使用心得及排行榜綜合資訊的主流網站，隸屬於日本上市公司集團istyle Inc.。除日本、台灣外，在香港、大陸、韓國、美國等地，亦有集團旗下化妝品社群/電商/零售等相關事業營運。 網路產業隨著科技的不停進步，許多新技術不斷創新，加上AI重塑了工程師的日常工作樣貌，利用AI協作，大幅提高工作效率，而「整合應用」則成為了新一代工程師的必備能力，學習各式工具並透過排列組合，優化/解決當前遇到的各式問題。 為維運@cosme TW、@cosme HK及整體Global平台系統，技術研發主要分成三部分： Ruby on Rails網站相關技術：利用ROR、HTML、JS、CSS持續開發網站功能。大數據相關技術：利用MongoDB自行開發Data Management Platform，並應用於數據分析、廣告投放、個人化推薦、OneID辨識等地方。AI相關技術：導入LLM應用於@cosme平台，啟動AI賦能，將現行服務+AI。

Our Product Vulcan is a cybersecurity solution specifically designed for GenAI, offering two core services: Red Team (vulnerability assessment) and Blue Team (real-time defense). It ensures GenAI compliance, cybersecurity robustness, and operational integrity. Since its official launch in 2024, Vulcan has been recognized by the international standard-setting organization OWASP as a certified vendor for LLM GenAI security testing and assessment. It is one of the few solutions capable of supporting multiple Asian languages (Traditional Chinese, Simplified Chinese, Japanese, Korean, Thai) and Standard Arabic. Learn more about us 👉 Vulcan product: https://vulcanlab.ai/Vulcan LinkedIn: https://www.linkedin.com/company/vulcanlab-ai/AIFT group: https://aift.io/ About the role We are seeking an experienced Machine Learning Lead to helm our Machine Learning team.In this pivotal role, you will be the engineering architect behind Vulcan’s core AI capabilities. You will act as the nexus between Research, Platform, and Product. Your mission is to translate cutting-edge findings on GenAI threats into robust, production-ready machine learning models that power our GenAI Security Guardrails (Blue Team) and Automated Vulnerability Assessment (Red Team).Crucially, you will serve as the bridge between deep tech and business strategy, articulating technical constraints (like FLOPS and latency) to leadership and clients while guiding the engineering direction. Key Responsibilities1. Model Development Optimization (Training Fine-tuning): Research to Production: Collaborate with the Security Research Team to operationalize new threat detection techniques. They identify the "what" (e.g., new prompt injection patterns); you determine the "how" (model architecture, training strategy). Fine-tuning Adaptation: Lead the fine-tuning of Language Models (e.g., using LoRA/PEFT) to optimize for our supported muti-lingual languages and specific security intents. Multimodal Readiness: Prepare the system for Multimodal (Text + Image/Audio) capabilities. Evaluate and implement models to detect visual prompt injections and non-textual threats as the product evolves. 2. MLOps Data Infrastructure: Enhance Scale MLOps: Take ownership of our existing ML pipelines. Focus on optimizing and scaling CI/CD/CT workflows to improve training efficiency and deployment velocity. Data Governance: Implement and enforce rigorous Data Versioning strategies (e.g., DVC) to ensure complete reproducibility of model artifacts and datasets. Monitoring Reliability: Maintain rigorous monitoring for model drift and performance, ensuring high reliability in a production security environment. 3. Cross-Functional Implementation Leadership: Platform Collaboration: Work closely with the Platform Engineering Team to integrate ML models into the broader product architecture. Ensure seamless interaction between model inference services and the main platform logic. Team Leadership: Lead and mentor Machine Learning Engineers, fostering a culture of engineering rigor, code quality, and operational excellence. Resource Management: Manage GPU resources and compute budgets effectively for both training and inference workloads. 4. Technical Strategy Stakeholder Management: Translating Tech to Business: Act as the technical voice of the ML team. You must effectively explain complex ML concepts (e.g., FLOPS, quantization trade-offs, model latency vs. accuracy) to executive leadership and clients. Cost-Benefit Analysis: Justify compute resource investments. Articulate the trade-off between infrastructure costs (GPU hours) and performance gains to non-technical stakeholders. -

在 Pinkoi，工程師的任務是讓每個來 Pinkoi 的人都能擁有難以忘懷的使用體驗，你必需擁有極大的熱情，因為我們相信一個令人讚賞的網站服務，是由背後每一位工程師努力的追求卓越，每一個小細節都是 Pinkoi 非常在乎的事情！Pinkoi 致力於打造流暢且量身打造的探索與購物體驗，讓顧客輕鬆發現感興趣的商品、品牌與內容，並加深與平台的連結。同時運用創新的 AI 技術與深厚的產業知識，幫助品牌提升銷售業績、使規模快速成長，成為設計品牌邁向規模化、國際化不可或缺的重要夥伴。工作內容與挑戰維護和迭代網站底層架構，包括正式環境和開發環境，例如：CI/CD 流程、程式語言迭代、資料庫架構調整...等。協助建立與優化內部平台工具，提升開發者體驗。設計與維護監控、告警與可觀測性（logging / metrics / tracing）。產出高品質、穩定、可維護且可讀性高的程式碼，並養成良好的自動化測試習慣。能夠順暢地與各種領域的夥伴溝通合作，例如前端工程師、後端工程師、App 工程師、資料工程師等。擁有快速辨識系統問題的能力，並且能夠確實修復問題。持續改善系統架構、效能與穩定性，並樂於撰寫技術文件、分享知識，提升產品開發體驗。持續研究並導入新技術（如 Cloud Native 工具、AI 輔助開發）與創新想法，並評估其在實際環境中的落地與價值，創造更大的影響力。我們希望你有的特質充滿熱情，你想要做出世界級一流的產品。樂於學習，對於新技術抱有好奇以及開放的態度。良好溝通，能夠清晰地和 Pinkoi 的夥伴們溝通你的想法。主動積極，能發掘系統上的不足或可以更好的地方，並提出改善作法。自我要求，具備高標準、時限觀念和責任感。應徵條件有 2 年以上後端開發經驗，具備開發與維護系統的能力。具備良好的程式基礎，並樂於持續精進（Pinkoi 主要使用 Python，但我們歡迎任何程式語言的使用者來應徵）。對資料庫、資料結構以及演算法有基礎的理解，知道它們如何影響你的程式效能。對 Linux 作業系統有基礎的理解，特別是針對 Process 跟 Thread 的部分。熟悉 container 相關技術（例如：Docker、Kubernetes）。加分條件應用程式效能校調相關經驗。具備 Observability 相關經驗（Prometheus, Grafana, OpenTelemetry）。熟悉使用如 MySQL、Elasticsearch、Redis 等常見服務，並了解在設計與開發中需針對其分散式特性（如一致性、可用性、效能瓶頸）做出相應考量。熟悉以 LLM 工具輔助開發，並整合至日常工作中以提升效率與品質。熟悉雲端平台與基礎設施維運（AWS / GCP / Kubernetes / CI/CD pipeline）。熟悉 Cloud Native, Kubernetes 生態系（Helm, ArgoCD, Operators 等）。＃不用想了，趕快來當個 Pinkoi 人如果你有信心能夠勝任這份工作，歡迎提供你的個人履歷及小作業回答，即刻應徵！

【關於這個角色】核心任務是打通 LLM 與應用程式之間的溝通橋樑。你需要使用 Java 實作 Model Context Protocol (MCP Server)，讓 AI Agent 能夠安全、標準化地存取我們的資料與工具。 【你將面臨的挑戰】 Protocol Implementation: 開發與優化 MCP Server，確保與 LLM Client 端的通訊順暢且低延遲。Backend Development: 負責 API 的設計與實作，處理複雜的資料流邏輯與外部 API 整合。System Stability: 透過 Docker 容器化技術確保環境一致性，並透過完整的測試代碼（Unit/Integration Test）保障系統品質。

MoMo is the market leader in mobile payments in Vietnam. We strive to make all transactions fast, easy and joyful. We are looking for an experienced AI Engineer to join our growing Big Data AI team. At MoMo, we make AI/Machine Learning the core component to almost every part of the product - product recommendation, personalization, conversational AI, eKYC, risk scoring, fraud detection, promotion targeting and financial services. As a Senior AI Engineer, you will play a leading role in developing our Customer Service Chatbot system, delivering intelligent and seamless support experiences to millions of users.Mô tả công việcDesign, build, and optimize LLM-powered chatbot systems for customer service at scale;Develop and implement RAG (Retrieval-Augmented Generation) pipelines, prompt engineering strategies, and agentic workflows for domain-specific performance;Architect conversation flows, intent handling, and dialogue management systems that handle complex multi-turn interactions;Build evaluation frameworks and monitoring systems to measure chatbot quality, detect hallucinations, and ensure response accuracy;Collaborate cross-functionally with product, customer service operations, and engineering teams to continuously improve chatbot capabilities;Write production-grade code and maintain robust, scalable AI systems serving millions of users;Stay current with LLM advancements and evaluate new models, techniques, and tools for potential adoption.Yêu cầu công việc5+ years of experience as an AI Engineer, with at least 2 years focused on LLM applications or conversational AI systems;Deep understanding of LLM architectures, capabilities, and limitations (GPT, Claude, LLaMA, etc.);Experience building chatbot or virtual assistant systems, particularly for customer service use cases;Fintech domain experience is a strong plus;Proficiency in RAG systems, vector databases, embedding models, and prompt engineering techniques;Strong software engineering skills in Python. Experience with LLM tooling (LangChain, LlamaIndex, etc.);Experience with system design for high-availability, low-latency services;Familiarity with evaluation methods for generative AI systems and conversation quality metrics.