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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

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. -

[About Us 醫療X科技] 慧康生活科技 Health2Sync 成立於 2013 年，旗下擁有「智抗糖 App」與「雲端智慧照護平台」兩大產品，是同時具有B2B2C的數位新創團隊。主打產品「智抗糖App」為亞洲最大慢性病管理平台，提供個人化並可複製的慢性病管理方案，建立新一代的數位療法，這套數位醫療解決方案在全球累計已有超過百萬名使用者。我們的服務結合簡易操作的數位工具與個人化及自動化的即時分析，串連慢性病友的關懷照護網路與生活數據，協助糖友透過 App 自我管理血糖，並讓家人與醫療單位透過「雲端照護平台」更即時瞭解狀況並提供關懷。透過這套解決方案，我們積極串起糖尿病照護生態圈，連結藥廠與病患，讓藥廠提供個人化的衛教及介入 (engagement)，進而提升用藥的依從度，讓病患能有較好控制效果。[ About Our Team ]在數位醫療領域中，數據團隊是不可或缺的角色。作為H2數據團隊的一員，你將有大量的機會接觸到多樣化的生醫數據，通過數據分析探索及機器學習技術，最終的數據產品將可以直接回饋給用戶或醫療院所，讓數據發揮最大的價值。另外，數據團隊也有機會參與公司的重大決策，你的分析成果將會影響產品的走向及各項商業發展。在我們團隊中每個人都有機會一起發想及創造全新的數據產品，同時每個人的意見在團隊中都是非常重要的。期待在數據科學領域有豐富經驗的你可以加入我們，一起學習如何用數據科學相關的技術，為病患及醫療人員開發更多有價值的數據產品。 [Job Description]- 推動數據科學專案，以優化H2 產品。- 利用數位健康數據開發並部署機器學習, 統計模型及生成式 AI (GenAI) 應用。- 針對產品及分析應用，構建並維護基於大語言模型 (LLM) 的應用。- 優化並維護現有的 AI 系統，確保其性能與可擴展性。- 建立並改進數據基礎設施（data pipeline, data lakehouse), 以支援數據分析與建模。- 透過分析工具與統計方法，支援產品及業務團隊任務。

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。

請至均一網站投遞此職缺 工作內容與職位需求 工作內容 後端系統開發與維運：設計與實作 JUTOR AI 英文家教平台的後端服務、資料模型與 API；維護 Hexagonal Architecture，確保系統穩定、可測試、可維護。AI 功能整合：串接 OpenAI API，開發 AI 驅動的學習功能（作文批改、口說對話、聽力練習等）；運用 Langfuse 進行 Prompt 版本管理與效果追蹤。前端功能支援：使用 Next.js + React 開發學習模組 UI，串接後端 API，改善使用者體驗。Vibe Coding 正規化：接手團隊中非工程夥伴使用 AI 工具（如 Claude Code）開發的 MVP 原型，理解其市場洞察，並將其正規化為可維護、可擴展的產品功能 工作優缺點（來自內部夥伴的心聲） 優點 1. 小而精的產品團隊（1 PM + 1 前端 + 1 後端），決策快、迭代快 2. 技術架構現代化：Next.js 15、React 19、Python 3.12、Litestar、Hexagonal Architecture 3. AI 原生產品，深度整合 LLM 的教育應用，不只是表面功能 4. 團隊擁抱「Vibe Coding AI Agentic Coding」文化，支持善用 AI 工具提升效率 5. 重視程式碼品質：code review、自動化測試、CI/CD 完整流程 6. 做有意義的事：幫助台灣國高中生用更好的方式學習英文 7. 親子友善，具備遠端工作的彈性 挑戰 1. 團隊規模小，需要獨立作戰、一人多工 2. 需要適應「從 MVP 到正規化」的開發流程，接手非工程師產出的原型 3. 沒有壁壘分明的職責界線，需要在模糊的環境中展現主動積極的特質 能力要求 必要條件 1. 具有 3 年以上後端開發經驗，能獨立完成功能從設計到上線 2. 熟悉 Python 或同等主流語言，能快速上手現代 Web 開發框架 3. 具備 GCP 或 AWS 等雲端部署經驗，理解容器化與 CI/CD 4. 擅長寫測試自動驗證、code review，重視程式碼品質 5. 已經在用 AI 工具提升開發效率（Copilot、Claude、Codex 等），不是「有興趣學」 加分條件 - 熟悉 Hexagonal Architecture 或 Clean Architecture - 具有 LLM 應用開發經驗（Prompt Engineering、Agent Skills） - 熟悉 Next.js / React，能支援前端開發 - 具有 EdTech 產品經驗，或對教育議題有長期關注 人格特質 能在模糊中找到方向，不需要等待完整規格開放的態度，願意接手別人的產出，先理解再優化對「讓學習更好」這件事有基本的認同感 工作待遇 薪資範圍 月薪 60,000 元至 85,000 元，實際薪資依面試結果而定。 福利待遇 除勞基法規範應有假別，入職即享有第一年 4 天特休假，並且每年度皆有 3 天全薪事假 + 3 天全薪家庭照顧假。每人每年 5,000 元學習補助；辦公室隨時補充新書。入職即享有兩年一次的 6,000 元健康檢查補助。支持夥伴的心理健康，夥伴可定期申請「均陽全人關懷輔導教育協會」的協談服務，由組織提供支持。關心夥伴工作以外的生活，提供婚、喪、生育津貼。每年一次國內兩天一夜員工旅遊、一次春酒或尾牙，保證不談工作，只有吃喝玩樂！ 工作模式＆環境 表定上班時間為週一至週五 10:00 - 19:00，在信任夥伴當責的前提下，可自由規劃彈性工時。混成式辦公盛行，只要與協作團隊有共識，夥伴能自由選擇辦公地點，遠距也能保持高效！（進辦頻率以各職務面談討論為準）辦公室位於總統府旁，捷運西門站步行 3 分鐘，生活機能便利。正職夥伴入職即可申請電腦採購，不需自備工具。以 Slack 作為主要溝通工具。每月一次「均一日」，與大家輕鬆吃吃喝喝，分享彼此的工作里程碑！每季一次 Team Building 補助，與同組夥伴定期聚聚！ 團隊文化 高度彈性、成長思維的敏捷團隊，重視四大核心價值觀「誠信、多元、恆毅力、推論與成果導向」；決策的思考以使用者（學生、教師、親屬）能否被有效協助為優先考量。組織扁平透明誠信，鼓勵不同想法的激盪；尊重每個人的專業，鼓勵「用愛心說實話」，努力創造橫向、上下都暢通的溝通管道。每半年一次 Review，與 mentor、密切協作的夥伴一起回顧一年的成長與挑戰，給彼此最棒的回饋。 申請方式 請至均一網站投遞此職缺 申請準備資料 履歷LinkedIn作品集 (GitHub、Blog)（加分）任何展現你「務實地用 AI 加速開發」的案例申請流程 申請流程 書審：填寫申請表單，讓我們對你有初步的認識。一面前導聊聊筆試：收到申請資料後，在進入面試前，和 CTO 快速的線上聊聊。兩次面試：我們會主動通知是否進行實體面談；面談將進行至少 2 次，通過後，你將和一群志同道合的夥伴一起發揮社會影響力！ 通知時程 不論書審結果為何，我們將盡快以電話或電郵聯繫回覆，請留意來電以及收件。若於二週內未收到回覆，請來信提供大名、申請職位確認。 請至均一網站投遞此職缺 了解更多均一人故事 是否該將系統升級？工程師該怎麼推動基礎建設？—— 一場花費四年推動的系統升級（Python2-3） 用科技長才，成就自己與他人——專訪均一教育平台軟體工程師 Eva 打破框架的職涯發展道路 — 專訪軟體發展組夥伴 Justin、Eva 不只「教學」能幫助教育，我在均一走上教育 x 科技的軟體工程師之路—— 專訪軟體工程師宜陞 軟體專業 + 教育意義，我認為是完美結合 —— 專訪前 Mozilla 主管、現任均一軟體 leader 先祐在非營利組織實踐創業之路——專訪均一教育平台總監 YoungHello World ! 均一軟體組開發流程介紹建立前端開發準則，讓團隊能夠有效率的開發好維護的程式碼 —— 均一前端工程師宜陞技術分享更多故事請見 均一部落格

Google welcomes people with disabilities.Minimum qualifications: Bachelor's degree in Computer Science or a related engineering field, or equivalent practical experience. 2 years of experience with programming in Python, C++, Java, or 1 year of experience with an advanced degree in an industry setting. 2 years of experience with developing large-scale infrastructure, distributed systems or networks, or with compute technologies, storage or hardware architecture. 1 year of experience with Machine Learning (ML) infrastructure (e.g., model deployment, model evaluation, data processing, debugging). Preferred qualifications: Master's degree or PhD in Computer Science or a related technical field. 5 years of experience in working with multiple enterprise and cloud technology systems, designing solutions, or developing business applications. Experience in one of the Large Language Model (LLM) frameworks (e.g., NeMo Megatron, MaxText, etc.). Experience with Kubernetes or Slurm. About the jobGoogle's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.Responsibilities Create and deliver production solutions, best practice recommendations, tutorials, blog posts, and sample code for internal and external use. Work with early adopter customers. Provide customer and market feedback to product and engineering teams to help define product direction. Develop and deliver advanced enablement internally and externally. Work as part of an organization to contribute technical assets, prioritize and shape solution direction, while impacting business and bookings. 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.