Cake 找工作

公司介紹 我們是一支總部位於台北、放眼全球市場的量化科技團隊，專注於以自研低延遲基礎建設與演算法策略，在全球資本市場中創造穩定優勢。 團隊結合軟體工程、AI 研究與硬體加速技術（HPC／GPU／FPGA），打造奈秒級決策系統。每日處理龐大即時市場數據，並將研究成果直接轉化為可量化的交易成果。 這裡不是做 demo 或概念驗證，而是將模型真正部署在高壓、即時決策環境中。工程師能直接影響核心系統效能與策略收益，並在高度資源支持下快速實驗與迭代。 如果你期待的是： ✔ 真正落地的 AI 應用場景 ✔ 高品質數據與高算力資源 ✔ 與頂尖量化研究員並肩作戰 ✔ 成果與績效高度連動的回報機制 這將會是一個極具成長性的舞台。 工作內容 你將專注於建立與強化 LLM Agents 與 Reinforcement Learning 能力，直接應用於交易自動化與市場洞察： 與量化研究員共同設計實驗，將模型輸出轉為可交易訊號 建立 AI Agents（RAG、Tool Use、Task Planning）提升研究與交易效率 進行 Prompt Engineering、LoRA、Quantization、Distillation 等模型優化 針對金融文本（新聞、財報、社群、事件）進行 Fine-tuning 與 Alignment（SFT/DPO） 建立 Offline/Online Backtesting 與 A/B Testing 流程 導入 MLOps（CI/CD、Containerization、Model Versioning）提升模型治理能力 追蹤前沿 LLM 研究並進行內部技術分享 使用技術 Python / PyTorch / TensorFlow LLM 生態系：LangGraph、Ollama、OpenAI SDK Fine-tuning 技術：LoRA、MoE、Quantization、Distillation Alignment：SFT / DPO AI Agent Architecture（RAG、Tool Calling、Planning） HPC / GPU 加速環境 分散式數據處理與低延遲基礎建設 為什麼值得加入？ 真實高價值應用場景（模型直接影響交易決策） 高品質資料與充足算力資源 扁平透明文化，高自主權與技術決策影響力 績效高度連動的薪酬結構 國際市場布局與未來海外發展機會

公司介紹 這是一家高速成長的 AI 新創團隊，專注於 Physical AI 與 Industrial AI 的落地應用。團隊致力於打造能將真實世界工業環境快速轉換為高擬真模擬場景的 AI 平台，讓 AI 能在虛擬環境中進行訓練與策略優化，最終部署至真實工業系統。 公司產品結合 3D Simulation、Digital Twin 與 Reinforcement Learning 技術，讓企業可以在虛擬世界完成複雜系統的訓練與測試，大幅降低現實環境的成本與風險，並加速智慧製造與自動化的導入。 團隊由多位具創業與深度技術背景的成員組成，目前已獲得 國際級 AI 科技公司與知名投資機構支持，並與高端製造及半導體產業合作。工程師將有機會參與 AI + Simulation + Robotics 的前沿技術應用，直接將研究級技術落地至真實世界場景。 工作內容 作為 Senior Reinforcement Learning Engineer，你將負責透過強化學習技術優化自動化系統與工業場景中的 AI 決策能力，並在模擬環境中訓練可部署於真實世界的 AI 模型。 你將有機會參與 AI 在 工業自動化、機器人與智慧製造場景中的實際應用。 主要職責包含： 在 NVIDIA Isaac Sim 等模擬平台上建立與訓練強化學習模型 設計並實作 state space、action space 與 reward function 開發與優化 RL policy（如 Q-learning / Policy-based methods） 與 AI / Simulation / 3D 團隊合作進行系統模擬與模型訓練 持續調整模型與參數，提升策略效率與系統穩定度 將模擬環境中的最佳策略導入實際工業系統 使用技術 Python PyTorch / TensorFlow Reinforcement Learning Algorithms NVIDIA Isaac Sim Simulation / Digital Twin Robotics / Automation Systems

公司介紹 我們的客戶是一家專注於 Physical AI 與數位孿生（Digital Twin）技術 的 AI 新創團隊，致力於打造能夠讓 AI 在虛擬環境中訓練、學習並優化決策的下一代平台，並將最佳策略部署回真實世界場域。 團隊核心技術結合 AI、3D 模擬、運籌優化與大型場域建模，應用於智慧製造、自動化物流與高精密產業等場景，協助企業在虛擬工廠中完成策略模擬與 AI 訓練，大幅提升建置效率與營運決策能力。 公司獲得 國際 GPU 生態系與多家產業資本支持，並與大型科技與製造企業合作，是少數專注於 Sim-to-Real / Real-to-Sim AI 應用落地 的技術團隊。 如果你對 AI + Simulation + Robotics / Automation 的跨領域技術有興趣，這將是一個能直接參與核心產品與演算法設計的機會。 工作內容 你將加入核心演算法研發團隊，負責設計並優化應用於 大型數位孿生場域的演算法模型，協助解決複雜環境中的路徑規劃、排程與資源配置問題。 主要職責包含： 建立與設計演算法模型（如圖論、網格建模、路徑規劃或優化模型） 從 3D 環境與場域資料中建構抽象模型並設計解法 設計並實作高效能演算法模組（Python 為主） 使用 GPU 加速工具優化大型資料處理或模擬效能 與產品與工程團隊合作，將演算法整合至平台系統 測試與評估不同策略表現並持續優化 使用技術 Python CUDA / GPU Parallel Computing PyTorch Algorithm Design / Data Structures Graph Theory / Path Planning 3D Simulation / Digital Twin Optimization / Scheduling

HOYA BIT 致力成為加密貨幣新鮮人的最佳信任夥伴，我們致力研究加密貨幣的解決場景，並針對用戶需求提供解決方案，讓加密貨幣便利每個人的生活! ▎經營理念 享受工作與生活 當你踏入 HOYA BIT 後，你會發現我們致力讓員工創造與突破，高成就感與高報酬是讓每一個夥伴全力以赴的原動力! 高度成長與不斷創新 HOYA BIT 鼓勵每一位的夥伴不斷創新，唯有求新求變才能撼動市場，為此我們也提供每位夥伴學習經費，並透過每個月的內部交流及外部講座提升每一個夥伴的能力！ 客戶至上的服務模式 由於 HOYA BIT 是主打新手友善的加密貨幣交易所，所以我們以積極熱情的精神來服務我們的客戶，並致力透過每一個用戶的回饋來改善 HOYA BIT 的產品及服務，唯有熱情擁抱用戶，才能得到用戶的最高信任。 ▏我們相信越好的人才就需要越少的管理，所以在管理上我們只要求夥伴們尊重會議所決定的專案期程，在過程中若遇任何困難都請「即時提出」、才能「及時解決」，在辦公部份我們也致力打造讓大家都能舒適工作的環境。 ▏

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

General Summary: We’re seeking a multidisciplinary engineer with strong expertise in computer vision algorithms and SoC/hardware architecture. This role is ideal for someone who thrives at the intersection of cutting‑edge AI models and efficient hardware implementation. You’ll design segmentation algorithms, optimize modern deep learning architectures, and help shape the hardware that runs them. Responsibilities Develop and optimize computer vision algorithms, with emphasis on segmentation and real‑time performance.Implement and tune state‑of‑the‑art efficient AI architectures, including Transformers, Mamba‑style sequence models, and attention‑optimization techniques such as FlashAttention.Collaborate with hardware and SoC teams to co‑design accelerators and pipelines for CV and ML workloads.Profile and optimize model performance across memory, compute, and bandwidth constraints.Contribute to system‑level architecture decisions for next‑generation CV/AI products.Work closely with firmware and software teams to deploy models on embedded or edge platforms. Qualifications Strong background in computer vision, especially segmentation (classical and deep learning–based).Solid understanding of SoC architecture, including compute accelerators, memory hierarchy, and hardware/software interfaces.Hands‑on experience with modern deep learning architectures:Transformers and efficient transformer variantsFlashAttention or similar attention‑optimization techniquesMamba or other state‑space modelsSOTA efficient models (e.g., MobileNet‑style, ConvNeXt, lightweight segmentation networks) Proficiency in Python and C/C++, plus experience with ML/CV frameworks (PyTorch, TensorFlow, ONNX, OpenCV).Familiarity with hardware modeling, FPGA prototyping, or RTL design is a plus.Strong ability to work across algorithm, software, and hardware boundaries. Preferred Experience Algorithm–hardware co‑design for edge AIQuantization, pruning, distillation, or other model‑efficiency techniquesReal‑time CV systems or embedded AI deploymentPerformance profiling tools and hardware simulatorsMinimum Qualifications: • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.ORMaster's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.ORPhD in Computer Science, Engineering, Information Systems, or related field.

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.

Minimum qualifications: Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience. 5 years of experience in device driver development (e.g., Linux/Android Kernel or RTOS). Experience in GPU architectures (e.g., pipelines, memory hierarchies, and command submission). Experience with graphics or compute APIs (e.g., Vulkan, OpenGL ES, or OpenCL). Preferred qualifications: Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture. 8 years of experience with GPU Compiler interactions or Low Level Virtual Machines (LLVM)-based backends or GPU performance improvement. Experience with pre-silicon emulation environments (Palladium, Zebu, or Veloce) and developing and debugging native code on Android. Knowledge of Memory Management Units (IOMMU/GMMU), power management, and interrupt handling. Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch) and how they leverage GPU kernels. Track record of shipping production-quality drivers for high-volume consumer electronics. About the jobBe part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration. As a Senior Graphics Processing Unit (GPU) Silicon Engineer in the Google Silicon team, you will be at the forefront of defining how our custom-designed hardware interacts with the entire software stack. You will drive the architecture and implementation of kernel-mode and user-mode drivers that power everything from high-end mobile graphics. You aren't just writing code, you are bridging the gap between hardware intent and software execution.Responsibilities Design, implement, and maintain GPU drivers (Kernel and User mode) for custom Google Silicon. Lead the 'first-light' activities for new GPU IP on pre-silicon (emulation/FPGA) and post-silicon platforms. Profile and optimize the driver stack to eliminate bottlenecks, reduce overhead, and improve power efficiency. Implement and support industry-standard Application Programming Interfaces (APIs) such as Vulkan, OpenCL, and potentially proprietary compute extensions for Machine Learning/Artificial Intelligence (ML/AI). Partner closely with GPU Architects, Register-Transfer Level (RTL) Designers, and Operating System (OS) teams (Android/Linux) to influence future hardware features and software interfaces. 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.

This role requires you to work in a shift pattern or non-standard work hours as required. This may include weekend work.Minimum qualifications: Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience. 6 years of experience with writing code in one or more general purpose programming languages (e.g., C++, Java, Python, Go, etc). Experience with Linux/Unix systems with debugging issues across the hardware/software boundary on enterprise-grade server infrastructure. Experience in troubleshooting for customer needs, and triaging technical issues across the stack (e.g., hardware faults, networking, virtualization, kernel drivers, firmware, performance). Preferred qualifications: Experience in working with distributed systems with the knowledge of common solutions, design patterns, or best practices. Experience in working with Artificial Intelligence/Machine Learning (AI/ML) computing hardware, including Graphics Processing Unit (GPUs) or other accelerators. Experience with containerization and orchestration technologies like Kubernetes or Slurm. Experience with ML frameworks (e.g., TensorFlow, Pytorch), with the knowledge of the AI/ML training and inference lifecycle. Excellent troubleshooting and communication skills with attention to details. About the jobThe Google Cloud team helps companies, schools, and government seamlessly make the switch to Google products and supports them along the way. You listen to the customer and swiftly problem-solve technical issues to show how our products can make businesses more productive, collaborative, and innovative. You work closely with a cross-functional team of web developers and systems administrators, not to mention a variety of both regional and international customers. Your relationships with customers are crucial in helping Google grow its Cloud business and helping companies around the world innovate. In this role, you will own customer issues and provide specialized support to other teams. You will be a part of a global team that provides support to ensure customers can deploy their Artificial Intelligence (AI) and Machine Learning (ML) workloads on AI Infrastructure products. You will troubleshoot technical problems with hardware and software debugging, networking, Linux system administration, coding/scripting, and updating documentation. You will help the customer’s success in the AI/ML space by making improvements to the product, internal tools, processes, and documentation. You will help drive business growth by recognizing and advocating for the customers’ tests related to AI deployments.Responsibilities Manage customer’s problems through diagnosis, resolution, or implementation of new investigation tools to increase productivity for customer issues on AI/ML infrastructure. Develop an understanding of AI/ML workloads and underlying hardware architectures by troubleshooting, reproducing, determining the root cause for customer reported issues, and building tools for diagnosis. Act as a consultant and subject matter expert for internal stakeholders in Engineering, Business, and customer organizations to resolve deployment and operational obstacles in AI infrastructure environments. Work with multiple Product and Engineering teams to find ways to improve the product, and interact with our Site Reliability Engineering (SRE) teams to drive production. Be available for non-standard work hours or shifts which may include weekends as needed. 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.

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform. WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers and portfolio managers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people. The Role We are seeking an exceptional senior-level Python engineer to join a small team working on complex data pipelines, AI/ML systems, and cutting-edge software solutions. This role will be responsible for managing technical objectives, providing technical leadership, and maintaining a hands-on approach to development. The ideal candidate will work closely across teams within WorldQuant as part of our business-facing technology organization. A successful candidate will possess deep expertise in Python development, data engineering, software architecture, and design principles. They should be able to mentor junior team members, conduct code reviews, and drive architectural decisions. Experience with AI and large language models (LLMs) is highly desirable. What You'll Bring Master's degree or higher in Computer Science, Engineering, or a related technical field from a top-tier institution. 7+ years of experience as a Python developer, with a strong focus on data engineering and AI/ML systems. Expert-level knowledge of Python and its ecosystem, including experience with data processing libraries like Pandas, NumPy, and PySpark. Proficiency in designing and implementing scalable, maintainable, and efficient data pipelines. Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes). Expertise in version control systems (Git), CI/CD practices, and agile methodologies. Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders. Experience in the finance industry is a plus but not required. Experience with AI/ML frameworks such as PyTorch, or scikit-learn, LLM, agents or systems of agents is a significant plus. #LI-DN1By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction. Copyright © 2025 WorldQuant, LLC. All Rights Reserved.WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.