Cake 找工作

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

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

Mô tả công việcBuild and training pipelines for Generative AIImplement, optimize with state-of-the-art computer vision modelsCollaborate with teams to integrate computer vision algorithms into larger AI systems and applications.Stay up-to-date with the latest advancements in computer vision research and apply them to enhance our AI projects.Yêu cầu công việcFinal year students or fresh graduates with GPA above 3.2/4 or 8.0/10;Education: Top students from Vietnamese universityEnglish: IELTS 6.0, TOEIC 800, or Cambridge C1 (Nice to have)Experience: Fresh graduates or candidates with less than 2 years of experience.Employment Type: Full-time.Proficiency in programming languages such as Python, C++, or similar, along with experience in deep learning frameworks (e.g., PyTorch).

公司介紹 我們的客戶為台灣具代表性的證券公司，長期深耕數位金融與智慧投資服務，並積極透過資料治理與 AI 應用，打造新一代以客戶為核心的數位體驗。 近年持續推動數據平台化、AI 治理與個人化服務，已成功將數據轉化為實際的投資決策與客戶互動價值，是金融產業中少數能將數據治理真正落地的組織之一。 工作內容 規劃、建立並落實 資料治理（Data Governance）與 AI Governance 機制，確保 AI 應用的合規性與可持續性 主導 數據即服務（DaaS） 架構，推動數據平台化與跨單位數據共享 結合數位軌跡與客戶行為分析，發展個人化服務與精準客戶意圖場景 以業務目標導向規劃數據驅動的數位轉型，拓展數位金融生態圈 建立與管理客戶標籤體系，支援行銷、風險控管與服務優化 協助打造數據自動化 Pipeline 與視覺化 UI / UX，提升數據使用效率 帶領團隊或跨部門專案，推動數據與 AI 應用落地 使用的技術與工具 Python Oracle SQL Data Pipeline / Data Platform 客戶行為數據與標籤系統 （加分）TensorFlow、PyTorch、Hadoop （加分）Tableau、Power BI、JavaScript

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。

BẤM NÚT APPLY/ ỨNG TUYỂN ĐỂ XEM THÊM THÔNG TIN CHI TIẾTWhat You’ll Do AI Systems and Hardware-Aware Modeling Explore AI workflows and develop scripts/models that assist in IC calibration, prediction, or optimization.Specialized model building and fine-tuning for circuit exploration, design, validationContribute to prototyping and automation tasks involving Python, PyTorch, or other ML frameworks. System Integration Automation Participate in cross-functional work that brings together hardware, software, and algorithm layers.Assist with system-level test setups, data analysis, and verification tasks. Team Collaboration Technical Growth Join a collaborative team environment that encourages asking questions, sharing ideas, and thinking beyond your current domain.Work alongside experienced engineers and researchers to learn best practices and deepen your technical foundation. Why This Internship Matters This internship will give you: Real project experience in one of the world’s leading chip design environmentsExposure to Marvell’s core technologies, toolchains, and product workflowsThe opportunity to explore both depth and breadth—whether you love transistor-level design or aspire to innovate at the system/AI levelA mentorship path that could evolve into a full-time role or thesis opportunity Your Path Forward Many of our interns go on to become key contributors and technical leaders within Marvell. If you’re dreaming of a career that spans deep analog design, AI-driven innovation, and system-level impact—this is where you start.

Mô tả công việcArchitect end-to-end generative AI solutions including Large Language Models (LLMs), multimodal AI systems, and AI-powered applicationsDesign and implement scalable generative AI systems leveraging state-of-the-art models such as GPT, Claude, Llama, and other foundation modelsBuild production-ready generative AI products including conversational AI, content generation, code generation, and intelligent automation systemsDevelop and optimize LLM fine-tuning, prompt engineering, Retrieval-Augmented Generation (RAG), and model alignment techniquesLead cross-functional collaboration with data scientists, ML engineers, product managers, and business stakeholders to deliver complete AI solutionsEstablish MLOps practices for generative AI including model versioning, A/B testing, monitoring, and continuous deploymentMentor engineers and provide technical leadership in generative AI best practices and emerging technologiesResearch and evaluate new generative AI techniques, tools, and frameworks to maintain competitive advantageEnsure responsible AI practices including safety, fairness, privacy, and ethical considerations in all AI systemsYêu cầu công việc3+ years of relevant professional experience in AI/ML with 2+ years specifically in Generative AIDeep expertise in Large Language Models, transformer architectures, and generative AI techniquesHands-on experience with foundation models (GPT-4, Claude, Llama, Gemini) and fine-tuning approaches (LoRA, QLoRA, PEFT)Production experience with generative AI applications including RAG systems, AI agents, and conversational AIStrong programming skills in Python with proficiency in PyTorch, Transformers, LangChain, and modern AI frameworksExperience with cloud platforms (AWS, GCP, Azure) and AI/ML services for model deployment and scalingLeadership experience in guiding technical teams and driving AI product development

AI Engineer with full-stack capabilities in Computer Vision and NLP, supporting the building, testing, and deployment of machine learning models and algorithms. The role works closely with senior engineers and cross-functional teams (product, marketing, data science) to integrate AI features into user-facing products and internal tools. Responsibilities also include improving AI pipeline performance, monitoring and evaluating deployed AI systems in operation, and assisting in the development of AI-powered internal tools such as assistant bots for content generation, marketing workflows, and other internal processes.Mô tả công việcDevelop and test AI-driven features in collaboration with the senior engineering team, focusing on marketing tools, user engagement, and automation products.Assist in building and improving internal AI tools, such as bots for content generation and workflow automation, to enhance team productivity.Support the deployment and maintenance of machine learning models and ensure their effectiveness in production environments.Continuously monitor AI systems and suggest improvements based on user feedback and system performance.Work in an agile environment, participating in sprint planning, development, and testing cycles.Yêu cầu công việcBachelor’s degree in Computer Science, Engineering, Mathematics, Data Science, or a related field.Basic understanding of AI/ML concepts and experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.Proficiency in programming languages like Python, with a solid understanding of coding practices and principles.Familiarity with data manipulation and analysis tools (e.g., Pandas, NumPy).Familiarity with cloud platforms (AWS, GCP, Azure) is a plus.Strong analytical and problem-solving skills, with a willingness to learn and adapt to new technologies and challenges.Good communication skills and the ability to work collaboratively within a teamExperience with project about Computer vision and NLP

The Senior Lead Storage and Server Test Engineer will play a pivotal role in the design, development, and execution of comprehensive test strategies for our AI data center's storage and server infrastructure. This leadership position requires deep expertise in enterprise storage systems, server architectures, networking, and a strong understanding of the unique performance and reliability demands of AI/ML workloads. The ideal candidate will be a hands-on technical leader, capable of mentoring junior engineers, driving test automation, and collaborating across engineering teams to deliver robust and high-performing solutions.Required Qualifications• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related technical field.• 3+ years of experience in hardware and/or software testing, with at least 5 years focused on enterprise-level storage and server systems.• Proven experience in a lead or senior technical role, mentoring and guiding other engineers.• Deep expertise in various storage technologies including NVMe, SAS/SATA SSDs/HDDs, RAID, distributed file systems (e.g., Ceph, Lustre, GPFS), SAN, and NAS.• Strong understanding of server architectures (x86, ARM, GPU servers), CPU/memory subsystems, PCIe, and power management.• Strong understanding of server architectures (x86, ARM, GPU servers), CPU/memory subsystems, PCIe, power management, and Baseband Management Controllers (BMC) functionality.• Proficiency in scripting languages (e.g., Python, Bash) for test automation and data analysis.• Experience with Linux operating systems (e.g., Ubuntu, CentOS, RHEL) and command-line tools.• Familiarity with networking concepts (Ethernet, TCP/IP, InfiniBand) and network testing methodologies.• Experience with test methodologies such as performance testing, reliability testing, stress testing, and fault injection.• Excellent problem-solving, analytical, and debugging skills.• Strong communication and interpersonal skills, with the ability to collaborate effectively across diverse teams.Preferred Qualifications• Familiarity with OCP (Open Compute Project)• Experience with cloud environments (AWS, Azure, GCP) and virtualization technologies.• Knowledge of containerization technologies (Docker, Kubernetes).• Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch) and their infrastructure requirements.• Experience with performance profiling tools (e.g., fio, Iometer, Perf, VTune).• Contributions to open-source projects related to storage, servers, or testing.• Certifications in relevant technologies (e.g., NetApp, Dell EMC, HPE, NVIDIA).

MoMo is the market leader in mobile payments in Vietnam, striving to make all transactions fast, easy, and joyful. You will join our Big Data AI team, where we position AI/Machine Learning as the core component of almost every product feature.Specifically, you will operate as a key technical leader in the Moni team—the squad behind MoMo's flagship AI Assistant. Moni currently serves hundreds of thousands of Monthly Active Users, scaling from a chatbot into a fully autonomous AI Agent. As a Senior / Technical Lead, you will drive the architectural decisions and engineering standards that power the next generation of our Agentic AI.Mô tả công việcTechnical Leadership Architecture:Define the technical vision and architecture for autonomous AI Agents.Make critical decisions on tech stacks, model selection, and system design to ensure scalability and reliability.Architect Build AI Agents: Lead the end-to-end development of complex Agentic workflows (Tool Calling, Planning, Reasoning) that integrate deep into the MoMo ecosystem.Multi-Agent Orchestration: Design and implement orchestration layers where multiple specialized agents collaborate to solve intricate user financial tasks.Advanced RAG Strategy: Engineer robust RAG pipelines (Hybrid Search, GraphRAG, Re-ranking) to handle vast knowledge bases with high precision.System Evaluation Quality Assurance: Establish "Gold Standard" evaluation frameworks for Agentic AI (reasoning capabilities, hallucination rates, safety metrics) and drive the optimization loop.Mentorship Best Practices: Mentor senior/junior engineers, conduct code reviews, and set high standards for code quality, MLOps practices, and GenAI engineering across the team.Production Excellence: Partner with DevOps/MLOps to ensure high availability and low latency for AI services serving massive concurrent traffic.Yêu cầu công việcExperience: 5+ years of professional experience in AI/ML/Software Engineering, with a strong track record in leading technical initiatives.Agentic AI Mastery: Deep hands-on experience in building AI Agents and Multi-Agent systems. Proficient in Agentic Design Patterns like Tool Calling, Planning and Reasoning, and frameworks such as LangChain, LangGraph, or Agents SDK.Advanced RAG Search: Expert knowledge of retrieval strategies, vector databases, and semantic search optimization.LLM Model Strategy: Strong capability in selecting and benchmarking Foundation Models (Open vs. Closed source) and applying fine-tuning/alignment (RLHF, DPO) strategies.System Evaluation: Experience implementing rigorous evaluation pipelines for Agentic AI (using Ragas, Langfuse, or custom metrics).Engineering Excellence: Proficient in Python, PyTorch, and modern Data/AI stacks. Experience in designing high-load distributed systems is a plus.Leadership Mindset: Ability to navigate ambiguity, drive technical consensus, and balance engineering perfection with product delivery speed.