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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. -

・與產品、風控、運營團隊協作，針對業務需求定義資料模型與監控指標・建置 ETL 流程，收集與清洗來自平台的行為數據（如下注記錄、轉碼、點擊行為）・開發與維護異常偵測模型（如洗碼對打、機器人行為、套利用戶）・利用機器學習或統計模型預測玩家留存、LTV、流失風險・設計風控策略，提升平台資金與行爲風險控制能力・定期產出分析報告，提出可行的產品或營運優化建議

Job Summary: You are responsible for contributing to the development of AI/ML solutions that will drive the innovation of our product offering. This entails understanding and AI model building, implementing and measuring the effectiveness of various AI/ML models in addressing various opportunities in the medical field. A proven track record of building AI projects over the past five years is essential. Job Responsibilities: Drive end-to-end ML projects from data engineering, machine learning model development/data analytics to deployment.Scope end-to-end requirements to ensure an efficient implementation of AI products.Work with the team to scope AI use cases and make sure that data is made available for analysis, articulate the needs of data scientists in the early stage of the project.Monitor AI project deployments, proactively identify risks, and coordinate with relevant parties to resolve issues.Work with the engineering team to design, execute, and monitor product experiments.Document and communicate findings to stakeholders in a clear and concise manner

About the Role We’re looking for a Senior AI Algorithm Engineer with a strong background in image processing and vision-language AI. You will lead the design and optimization of cutting-edge computer vision and inference algorithms, with applications spanning color analysis, image stitching, and multimodal understanding. This role requires hands-on experience in deep learning, cloud deployment, and production-level AI integration. You’ll also work with frameworks such as NVIDIA NeMo and deploy AI services using NIM to cloud platforms like GCP and AWS, with Kubernetes for orchestration. What You’ll Do Design and implement deep learning models for image processing, object detection, and anomaly detectionDevelop models for color recognition, color classification, and image-based feature analysis Fine-tune or integrate Large Language Models (LLMs) for vision-language tasks such as captioning, semantic search, and classification Optimize models for accuracy, inference speed, and resource efficiency Deploy and scale model services on GCP / AWS using Kubernetes (K8s) Utilize NVIDIA NeMo to train and deploy LLMs or VLMs, and package models into lightweight Docker containers served via NIM architectureCollaborate closely with product, frontend, and backend teams to integrate AI features into real-world applications

【職務核心】 您將利用海量數據構建核心決策模型，透過自動化手段解決內部的營運痛點。我们需要您具備將數學理論轉化為生產級 (Production-grade) 程式碼的能力。 數據煉金：使用 SQL 從龐大的資料倉儲中萃取 (Extraction) 有價值的特徵，並進行深度分析。模型開發與自動化：應用 Data Mining 與 ML 技術設計自動化工具，優化內部作業流程與決策效率。落地與維運：負責模型的容器化 (Docker) 封裝與部署，監控模型在正式環境的表現，確保系統的高可用性。技術顧問：與跨部門團隊協作，向非技術人員解釋 AI 模型的應用場景與邊界 (Limitations)。

開發與實作 生成式 AI 與影像辨識模型，用於產品瑕疵生成（Stable Diffusion、ControlNet、GAN 及其變體）、資料擴增與品質檢測。應用與微調 影像辨識／表徵學習模型（如 YOLO、CLIP、DINOv3 等新型開源模型）。進行 大型模型（ViT、LLM）Fine-tuning、模型建置、調校與效能優化。建立 資料清理、特徵工程、模型訓練與評估流程，持續提升模型穩定性與準確度。規劃並實作 RAG（檢索增強生成）架構，整合向量資料庫與 LLM。開發與維護 AI 模型服務 API，並與 WPF 前端及其他系統整合。進行 AI 技術與學術文獻研究，將研究成果應用於實務專案。使用 Docker、Git 進行部署與版本控管，配合主管交辦事項與團隊合作。依專案需求配合國外出差（一年約 1--3 次，每次約 3--4 週），參與專案導入、系統部署、模型調校或跨部門協作。其他主管交辦事項，並與團隊密切合作完成專案目標。必備條件3 年以上 AI／機器學習／深度學習 相關工作經驗，熟悉python、C#。熟悉 TensorFlow、PyTorch、Keras 等深度學習框架。熟悉 影像辨識模型與演算法，具 YOLO、CLIP、DINO（含新版本）等實作或應用經驗。具備 生成式模型（GAN 及其變體、Stable Diffusion、ControlNet）實務經驗，並理解模型底層原理。熟悉 Hugging Face 生態系（Transformers、PEFT、Datasets、Tokenizers）。有使用 PEFT 技術經驗（如 LoRA、QLoRA、Prefix Tuning 等），能在有限 GPU 資源下進行有效訓練與調校。了解 Fine-tuning 對模型效能、泛化能力與推論成本的影響，並能依量產需求進行權衡與最佳化。具備 RAG 架構、Prompt Engineering、向量搜尋與任一向量資料庫 經驗。具備 API 開發經驗，熟悉 Docker、Git。具備 數據清理、特徵工程、模型評估與效能優化能力。具良好溝通能力，可獨立作業並進行團隊合作。加分條件曾參與 產品瑕疵檢測、工業影像或製造業 AI 專案。具 影像生成＋影像辨識混合應用 經驗（如生成資料輔助訓練）。具 論文閱讀與模型重現（Reproduction）經驗。具 WPF 前端開發 或 AI 系統整合經驗。曾參與 AI 相關研究、技術分享或開源專案。具 對比學習（Contrastive Learning） 應用經驗（如 Self-Supervised Learning、Representation Learning）。有使用 StableDiffusion WebUI、ComfyUI經驗。

(About Us) We are a leading global IT services and consulting firm with a presence in 30 countries and a team of over 30,000 technology experts. As a long-term, trusted partner for Fortune Global 500 companies, we deliver cutting-edge digital transformation solutions, particularly within the finance, automotive, and manufacturing sectors. We are now seeking a passionate AI expert to join our elite team in Taiwan and pioneer state-of-the-art Generative AI projects. Position Highlights ✨Pioneer Enterprise AI in the Heart of the Finance IndustryThis is more than just a development role; it's a chance to build enterprise-grade Generative AI solutions for a major international financial client. You will apply the most advanced AI technologies to solve complex, real-world business challenges and gain incredibly valuable project experience in a high-impact domain. 🚀Master an In-Demand, Future-Ready Tech StackYou will work extensively with the Microsoft Azure AI ecosystem (including Azure AI Studio, Search, and Logic Apps), integrating it with today's most sought-after technologies like RAG, LLMs, and Kubernetes. This is a prime opportunity to align your skill set with the future of AI and stay ahead of the curve. 🤝Collaborate with a Global Team of AI ExpertsYou're not on your own. In this role, you will work in close collaboration with our headquarters' AI Center of Excellence (AIC). This gives you a unique opportunity to engage with top AI specialists, tackle world-class challenges, and expand both your technical perspective and your international professional network. 💡A High-Impact Role with Key Technical OwnershipAs a key technical member of the project, your expertise will directly shape the solution's architecture and success. You will have a substantial impact on the client's AI adoption strategy, offering you a highly visible platform to demonstrate your skills and drive tangible results. 🌍A Global Career Stage at a Top-Tier IT PowerhouseBecome part of an internationally acclaimed global IT group with over $1 billion in annual revenue. This translates to a stable and supportive environment, access to international resources, and a clear, transparent career path for your professional growth. (About the Role) This isn't just a development role; it's a unique opportunity to stand at the forefront of the AI revolution. As a core member of our team, you will directly shape the AI transformation roadmap for our major clients in the financial services industry. Your key responsibilities will include: Lead GenAI Solution Development:Design, build, and deploy enterprise-grade AI applications from the ground up, leveraging Large Language Models (LLMs) and advanced Retrieval-Augmented Generation (RAG) techniques to solve real-world business challenges.Build Robust MLOps Pipelines:Take ownership of the end-to-end machine learning lifecycle. You will construct automated pipelines for model training, versioning (MLflow), CI/CD, and production deployment on Kubernetes.Drive International Collaboration:Work closely with our AI Center of Excellence (AIC) in Vietnam, sharing insights, exploring new technologies, and applying them to high-impact projects in a truly global setting. (Our Tech Stack) Generative AI:OpenAI APIs, LLMs, RAG, Vector Databases (Qdrant)Cloud MLOps:Azure (AI Studio, AI Search, Logic Apps, Storage Account), Copilot Studio, MLflow, KubernetesProgramming Automation:Python, n8n

AI Engineering LLM Applications | Senior AI Engineer / Tech Lead - TL (Global Financial Group | Fluent English Required) Company Overview Our client is the Taiwan entity of a well-established global financial group with operations across multiple international markets. The organization is known for its strong governance, financial stability, and long-term commitment to technology-driven transformation. In recent years, the company has made significant investments in AI and data-driven initiatives, forming a dedicated AI team focused on delivering production-ready AI solutions that directly support core business operations and customer-facing platforms. This role involves frequent collaboration with overseas teams, making strong English communication skills essential. Responsibilities Lead AI Engineers and Software Engineers to design and deliver AI-powered solutions Apply Machine Learning and LLM technologies to real-world business systems (e.g., call center, telesales, customer interaction and call routing platforms) Collaborate closely with global stakeholders to understand requirements and drive execution Design, build, and maintain scalable, reliable, and secure AI services Ensure high code quality, system performance, and long-term maintainability Contribute to technical decisions, architecture design, and best practices Balance evolving priorities while maintaining delivery momentum Technologies Python (production-grade development) Machine Learning / Deep Learning(PyTorth, TensorFlow) Large Language Models (LLMs) Generative AI FastAPI, Uvicorn Docker, Kubernetes Distributed, high-throughput, low-latency system architectures CI/CD and cloud deployment experience is a plus

公司介紹 我們的客戶為台灣具指標性的大型金融機構，長期被市場視為金融科技與 AI 落地的領先者。近年在 Generative AI 領域投入大量資源，不僅推動多項 GenAI 旗艦方案，更成功將 AI 技術導入實際營運流程，建立可複製、可擴展的企業級應用模式。 本職缺隸屬於核心的轉型單位（約百人規模），高階長官具備資工博士級背景，組織定位關鍵、決策鏈短，並直接影響 AI 產品是否能安全、穩定地交付給最終客戶。 職務說明 我們正在尋找一位 AI 模型主管，從零建立企業級 AI 品質與評測體系。 你將擔任 AI 產品上線前的 「守門員（Gatekeeper）」，全權負責 LLM、RAG 與 ML 系統的評測標準、發布流程與風險控管，平衡模型效能、安全性與合規性，對產品能否正式上線具有關鍵影響力。 工作內容 一、AI 評測策略與框架建立 從零打造企業級 AI 評測架構，定義 LLM / RAG / ML 系統的核心評估指標 評測面向涵蓋：準確率、相關性、真實性（Faithfulness）、一致性（Consistency） 將 Responsible AI 原則納入驗收標準（公平性、偏見、可解釋性） 推動評測流程自動化，並與 MLOps / CI-CD 深度整合 二、基準測試與資料治理 規劃並管理 Golden Dataset，涵蓋關鍵業務流程、Edge Cases 與對抗性樣本 追蹤並評估主流評測工具與方法（如 RAGAS、DeepEval、Arize Phoenix） 建立模型版本間可比較、可追蹤的 Benchmark 體系 三、AI 安全與紅隊演練 建立 AI 安全防護與風險驗證機制 主導 LLM 紅隊演練（Red Teaming） 制定並驗證 Prompt Injection、Jailbreaking、PII 洩露等風險的防禦與壓力測試標準 四、跨部門協作與團隊領導 與演算法、後端工程、產品團隊密切合作，建立錯誤分析回饋迴圈 針對生產環境 Bad Cases 進行 RCA，提出 Fine-tuning / Prompt Engineering 優化建議 負責團隊培育、流程標準化與評測文件制度建立

About the Role:We are seeking an experienced Machine Learning Engineer to architect and own our end-to-end speech processing pipeline. In this role, you will bridge the gap between signal processing and generative AI, managing the flow from raw audio input to highly accurate transcription. You will be the primary owner of our ASR stack, with a specific mandate to optimize OpenAI’s Whisper for a high-throughput, low-latency cloud production environment.Key Responsibilities:1. Production ASR Architecture: Design and build scalable serving infrastructure using tools like Triton Inference Server, TorchServe, or vLLM to handle concurrent audio streams with minimal latency.2. Whisper Optimization: Push the limits of Whisper models in production. Implement distillation, INT8 quantization, and framework acceleration (e.g., Faster-Whisper, CTranslate2) to drastically reduce inference time without sacrificing accuracy.3. Advanced Noise Cancellation: Develop and integrate deep learning-based noise suppression models to pre-process audio. Your goal is to ensure high fidelity and low WER (Word Error Rate) even in complex, noisy acoustic environments.4. Model Fine-Tuning: Customize open-source ASR models (Whisper, Wav2Vec2, HuBERT) on our proprietary datasets to master domain-specific vocabulary, accents, and acoustics.5. Tech Stack Evolution: Actively evaluate and integrate the latest open-source audio models from the Hugging Face ecosystem to keep our stack on the cutting edge.