Cake 找工作

【團隊介紹】 我們是一個充滿熱情與創意的團隊，致力於結合科技與數據驅動保險業的創新變革。在這裡，你將與專業的技術與商業團隊協作，打造下一代智能解決方案，推動產險的數位轉型與智能化發展。 我們相信，未來的保險不僅僅是理賠和風險分攤，更是結合數據與AI技術實現全方位的風險預測與預防。 無論是車險理賠自動化、自然災害風險評估，還是風險預防方案，我們不僅在傳統產險領域引入前沿技術，也正在探索保險科技的無限可能。 如果你熱愛結合商業與技術，並希望將創意和洞察力轉化為可落地的AI解決方案，這裡將是你大展身手的最佳舞台！加入我們，與數據和科技共同塑造保險的未來！👀更多關於我們做的數據服務，期待您的加入，運用數據專案管理與技術整合能力，推動 AI 轉型與數據生態建構，讓數據創造最大價值！1. 九成跨域人才！國泰產險多元跨域、探索共融 打造數位數據轉型創新基地🔗https://www.bnext.com.tw/article/81887/cathay_ddt_2025012. 國泰產險推業界首創「CarTech智能車險加值服務」，數據驅動助法人車隊落實損害防阻🔗https://www.bnext.com.tw/article/81313/cathay-ins2024113. 國泰產險數位轉型新里程！AI與數據驅動加速全險種理賠、提升風控更有效阻詐2,300萬🔗https://www.bnext.com.tw/article/81460/samrtclaim_2024

公司介紹 這是一家正積極推動AI轉型與數據驅動決策的大型網路平台集團，致力打造以使用者為中心的多元生態服務。 內部AI團隊為企業智能化的核心引擎，五年內已成功建置超過數百項AI應用方案，廣泛應用於客服、內容生成、推薦系統與自動化決策等場景。 在這裡，你將與頂尖AI人才協作，從模型研發到產品落地，親手定義生成式AI於大型平台的真實應用價值。 工作內容 設計與實作先進的 ML/生成式AI 模型（如推薦系統、LLM、計算機視覺） 規劃並優化模型部署架構，確保高效、可擴展的AI服務 跨部門協作，將AI技術落地至產品與商業應用中 負責專案進度與品質管理，確保成果符合業務需求與技術標準 探索新興AI技術（RAG、多模態生成、模型微調等），推動持續創新 使用的技術 Machine Learning Frameworks：TensorFlow / PyTorch LLM Generative AI：RAG、Prompt Engineering、Fine-tuning Cloud Deployment：Kubernetes、Docker、CI/CD Pipelines Data Tools：Python、SQL、Feature Store、MLOps Pipeline

職缺介紹 晧飛思（Heph A.I Studios）是一家專注於 AIGC（AI 生成內容） 的創新公司， 致力於打造 數字人（Digital Human）、語音互動（Speech AI）、虛擬主持人（AI Host）、智慧櫃檯（Smart Concierge）、虛擬助理（AI Assistant） 等新世代 AI 產品。 我們的 iOS 應用正引領 AI 互動的新世代， 讓使用者能以自然的語音、表情與情感與智慧角色交流。 如果你對 AI 技術與人機互動體驗 充滿好奇， 並希望在產品從 0 到 1 的建構過程 中實際參與與學習，這個職位將非常適合你。 工作內容 協助開發與優化 數字人、語音互動、AI 內容生成 相關的 iOS 應用程式 參與 虛擬主持人（AI Host）、智慧櫃檯（Smart Concierge）、AI 助理 等產品模組開發 與資深工程師合作，整合 AIGC 技術（LLM、VLM、Stable Diffusion 等）至 iOS 應用協助串接 語音 AI 技術（Speech-to-Text / Text-to-Speech）與即時影音串流功能 撰寫乾淨、可維護的 Swift / SwiftUI 程式碼協助進行 App 性能優化與除錯參與 Code Review、技術討論與跨部門協作 基本要求 一年以上 iOS 開發經驗，熟悉 Swift 與 SwiftUI 理解 Combine、Async/Await、Concurrency 等非同步開發概念 熟悉 MVVM / TCA / Clean Architecture 架構設計概念 具備基本影音處理經驗（AVFoundation / Core Image / Vision 佳）了解 RESTful API、WebSocket 串接流程 熟悉 Git 版本控制與 CI/CD（Fastlane / Jenkins）流程者佳 對 AI、語音技術、虛擬角色或互動應用有興趣 具備良好的學習能力、主動性與團隊合作精神 加分項目 曾開發或參與 AI 互動類、虛擬角色或創新應用專案 有 CoreML / TensorFlow Lite / PyTorch Mobile 使用經驗 熟悉 Whisper、VITS 或其他語音相關 AI 技術 對 ARKit / RealityKit / Unity 有基礎了解 有個人專案、開源貢獻或技術作品集可展示 成長與挑戰 在晧飛思，你將在實戰中快速成長，從「執行者」逐步成為「創造者」。 你將有機會： 與 設計師、資深工程師 一起打造新世代 AI 應用 參與產品與團隊 從 0 到 1 的建構過程，理解一個 AI 應用如何誕生 實際接觸 語音 AI、Vision Model、LLM 等前沿技術 在實務中累積產品開發與架構經驗，建立屬於自己的技術方向 我們重視實作與學習潛力，而非僅僅履歷。 若你熱愛開發、樂於探索新技術，我們會提供足夠的引導與支持，陪你一起成長。 這裡的挑戰，來自未知與創新； 而你的成長，將來自讓技術真正落地、讓世界看見你的成果。 薪資與福利 薪資範圍： 年薪 NT$80 – 130 萬（依能力與經驗調整） 年節績效獎金 休假制度： 除法定特休外，另提供彈性休假，可自由運用於休息、進修或個人規劃 假期項目： 生理假、婚喪喜慶假、育嬰假 員工生活： 年度旅遊補助、每月零食預算、員工餐點折扣方案 成長支持： 專業課程補助、內部技術分享與跨部門交流會 工作型態： 彈性上班時間與遠端工作選項

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

We are seeking a Senior AI Research Engineer specializing in Speech to join our AI RD team. You will lead research and development of advanced speech technologies, including automatic speech recognition (ASR), speech understanding, and text-to-speech (TTS) systems. Your work will contribute to voice-enabled assistants, call-bot intelligence, and multilingual speech interfaces, directly impacting millions of MoMo users across Vietnam. You will explore cutting-edge models, adapt them to Vietnamese and low-resource settings, and develop efficient, production-ready speech systems optimized for mobile and real-time environments.Mô tả công việcResearch and develop speech recognition models (ASR) for Vietnamese and multilingual contexts, focusing on noise robustness and real-time performance.Design and train speech understanding systems for intent detection, speaker classification, and dialogue comprehension.Develop text-to-speech (TTS) pipelines with natural prosody, emotion, and style transfer for human-like synthesis.Optimize model performance for low-latency deployment on mobile and edge devices.Integrate ASR, TTS, and NLU modules into end-to-end speech assistants and call-bot systems.Collaborate with backend and product teams to integrate speech technologies into MoMo’s ecosystem (e.g., customer service, virtual assistant).Conduct literature reviews and lead experimental studies on speech processing.Yêu cầu công việcQualificationsBachelor's or Master's degree in Computer Science, Electrical Engineering, Artificial Intelligence, or related field. PhD is a plus.Proven experience in speech processing research or development, such as ASR, TTS, or spoken language understanding.Strong knowledge of deep learning for audio.Hands-on experience with frameworks like PyTorch, TensorFlow.Proficiency in Python and familiarity with signal processing libraries.Understanding of model deployment and optimization for real-time inference.Ability to read, reproduce, and extend state-of-the-art speech research papers.Nice to HaveExperience with end-to-end speech systemsExperience in Vietnamese or Southeast Asian speech datasets.Familiarity with multilingual pretraining or self-supervised learningKnowledge of speech emotion recognition, speaker diarization, or voice conversion.Experience deploying models in production environments (e.g., on mobile apps or customer service systems).

We are seeking a Senior AI Engineer (AI-Ops / MLOps) to take a leading role in designing, deploying, and optimizing large-scale AI systems at MoMo. You will be responsible for building robust, production-grade infrastructure that enables fast iteration and reliable serving of LLMs, and speech modelsIn this position, you will lead AI deployment strategy, mentor junior engineers, and collaborate with AI researchers to bridge the gap between prototyping and scalable production — ensuring that MoMo’s AI innovations reach millions of users efficiently and safely.Mô tả công việcUtilize end-to-end AI infrastructure pipelines on top of existing MoMo infrastructure, from training to serving and continuous monitoring.Lead the design and implementation of high-throughput model serving systems (e.g., vLLM, Triton, TensorRT, ONNX Runtime) and model serving techniques (in-flight batching, speculative inference)Define model-level monitoring and alerting hooks integrated with MoMo’s existing observability stack (Prometheus, Grafana).Collaborate with DevOps/CloudOps teams, AI research, data engineering, and backend teams to ensure smooth integration of AI models into MoMo’s ecosystem.Conduct performance benchmarking and capacity planning to maintain SLA compliance across AI services.Focus on inference optimization strategies (quantization, batching, caching, pruning, GPU/TPU resource tuning).Mentor and guide the AI-Ops/MLOps team on best practices in distributed serving, orchestration, and infrastructure reliability.Evaluate new technologies and tools to improve scalability, cost efficiency, and model lifecycle automation.Yêu cầu công việcQualificationsBachelor’s in Computer Science, Artificial Intelligence, Software Engineering, or a related discipline.3+ years of experience in AI infrastructure, DevOps, or MLOps roles (with at least 1 years at a senior).Familiar with container orchestration (Kubernetes, Docker) and infrastructure-as-code (Terraform, Helm).Strong proficiency with Python and Bash scripting; experience with Go or Rust preferred.Proven experience deploying deep learning models (e.g., PyTorch, TensorFlow, JAX) at production scale.Hands-on experience with CI/CD systems (Jenkins, Argo CD, GitHub Actions) and monitoring stacks (Prometheus, Grafana, ELK).Strong understanding of distributed systems, load balancing, and high-availability architectures.Demonstrated ability to collaborate with researchers and translate prototypes into scalable, reliable production systems.Nice to HaveExperience with LLM inference optimization (vLLM, LoRA adapters, quantization, multi-GPU scheduling).Familiarity with speech or vision models and multi-modal AI pipelines.Experience integrating LLM and speech models into scalable inference microservices.Knowledge of feature stores, data versioning, and real-time feature serving (Feast, Redis, Kafka).Background in security, privacy, or governance frameworks for AI systems.

Minimum qualifications: Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience. 8 years of experience in Design Verification (DV). Experience in developing and deploying state of the art verification methodologies. Experience in any one of the hardware description languages (HDL) (e.g. Verilog/SystemVerilog). Experience with Python for scripting, automation, and data analysis in a verification context. Preferred qualifications: Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture. Experience with AI/ML frameworks and tools such as TensorFlow, PyTorch, or ONNX, particularly in how they relate to hardware implementation and verification. Understanding of modern verification methodologies (e.g., UVM, Specman, Formal Verification). Understanding of AI/ML fundamentals, including various neural network architectures (CNNs, RNNs, Transformers), ML algorithms, and concepts like training, inference, quantization, and activation functions. Excellent programming skills in Python. 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. Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.Responsibilities Integrate Machine Learning (ML) techniques into existing verification flows to improve efficiency, coverage, and debug capabilities. This could involve using ML for intelligent test case generation, bug prediction, or coverage analysis. Research, evaluate, and deploy new commercial and open-source verification tools, with a particular focus on those that support or enhance the verification of AI/ML designs. Work closely with AI/ML algorithm developers and architects to understand model behavior, data dependencies, and potential verification challenges, ensure effective integration into the verification environment. Identify opportunities to automate aspects of AI/ML verification, reduce manual effort and accelerate verification cycles. 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.

Minimum qualifications: Bachelor's degree or equivalent practical experience. 6 years of experience with cloud native architecture in a customer-facing or support role. Experience in pre-sales and consulting, delivering technical presentations, and leading discovery and planning sessions with customers with defined scope and success criteria. Experience with frameworks for deep learning (e.g., PyTorch, TensorFlow, Jax, Ray, etc.) and using machine learning APIs. Preferred qualifications: Experience in building and deploying data and Machine Learning (ML) pipelines with a focus on automation. Experience with prompt tuning and delivering successful prototypes. Experience in building machine learning solutions and leveraging specific machine learning architectures (e.g., deep learning, LSTM, convolutional networks, etc.). Experience working in technology sales within South East Asia region. Experience in understanding customer’s existing software workloads, with the ability to define a technical migration roadmap to the cloud reflecting specific customer needs. Ability to communicate in Bahasa Indonesia fluently to support client relationships in the region. About the jobThe Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners. As a Customer Engineer, you will partner with technical business teams as a subject matter expert in Artificial Intelligence and Machine Learning (AI/ML) to differentiate Google Cloud to the customers. You will help prospective and existing customers and partners understand the power of Google Cloud, develop creative cloud solutions and architectures to solve their business tests, engage in proofs-of-concepts, and troubleshoot any technical questions and roadblocks. You will engage with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud. You will partner with internal engineering stakeholders to improve products and build solutions, optimize for results when in production, and identify innovative ways to multiply the impact of the team as a whole.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Work with the team to identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers. Share in-depth AI/ML expertise to support the technical relationship with customers, including technology advocacy, supporting bid responses, product and solution briefings, proof-of-concept work, and partner directly with product management to prioritize solutions impacting customer adoption to Google Cloud. Work directly with Google Cloud products to demonstrate and prototype integrations in customer and partner environments. Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to successfully implement a complete solution on Google Cloud. Travel to customer sites, conferences, and other related events and act as a public advocate for Google Cloud. 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. 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. 5+ 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. By 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.

Google welcomes people with disabilities.Minimum qualifications: Bachelor's degree or equivalent practical experience. 5 years of experience with software development in one or more programming languages (e.g., Python, C, C++). 5 years of experience testing, and launching software products. 3 years of experience leading technical project strategy, ML design, and working with industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). 3 years of experience in performance analysis and optimization including GPU programming, mobile GPU, system architecture, performance modeling, benchmarking, machine learning infrastructure, or other similar experience. Preferred qualifications: Experience with ML frameworks (e.g., PyTorch, JAX, TensorFlow). Experience leading and delivering ML projects focused on on-device deployment (Android, iOS, web browsers, or embedded devices). Experience with on-device ML SDKs/tooling (e.g., TensorFlow Lite). Knowledge of ML converters/compilers and run-times, and hardware-accelerated ML inference techniques. Understanding of Generative AI model architectures and their optimization for on-device execution. Passion for innovation and for driving progress in on-device ML. 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. Our team focuses on model quality, outputs, compilation to achieve a wide range of capabilities on device, and work with other teams in the Laptops Tablets On-Device Machine Learning (LT ODML) to build APIs for building engaging user experiences on device. In this role you will be responsible for learning the foundations of ML modeling, neural networks, transformers, Generative Artificial Intelligence (genAI), optimization techniques like quantization, model compilation and op fusing, fine-tuning techniques like prompt tuning, and how they tie into the inference software stack to run across the entire laptop and tablet fleet of Android devices.ChromeOS delivers quality computing at scale to provide universal and unfettered access to information, entertainment, and tools. Our mission is to empower anyone to create and access information freely through fast, secure, simple, and intelligent computing.Responsibilities Bringup ML and GenAI models onto various compute (CPU, GPU and NPUs) across suite of devices (laptops and tablets). Test and benchmark model performance and quality across varying sizes and constraints. Work on fine-tune training and model quality optimizations along with model compilation and training. Build inference graphs that can leverage on-device models. Collaborate with power and performance teams to optimize model power/compute usage and memory footprint. 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.