Cari Lowongan

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。 ▏

【關於這個角色】你將擔任公司 AI 轉型的核心推手，負責將 AI 工具與流程真正「落地」到遊戲產業的日常運作中——從中央技術團隊的工具治理，到前線部門的實際應用推廣。【你會做的事】1. 跨部門 AI 需求訪談與規格收斂，將業務痛點轉譯為可執行的技術方案2. 擔任內部 AI 工具教育訓練講師，手把手引導非技術同仁上手 AI 工具3. 專案進度追蹤與風險控管（PMO），積極推動各項 AI 應用進程4. 識別各部門繁瑣人工作業，設計與導入 AI 自動化場景

Job Summary: As a Machine Learning Engineer, your responsibilities will include designing, developing, and deploying machine learning models and algorithms to address complex challenges and improve our products and services. Additionally, you will play a key role in AI-enhanced customer service. You will collaborate closely with data scientists, software engineers, and domain experts to implement state-of-the-art machine learning solutions. As a Machine Learning Engineer, your responsibilities will include designing, developing, and deploying machine learning models and algorithms to address complex challenges and improve our products and services. Additionally, you will play a key role in AI-enhanced customer service. You will collaborate closely with data scientists, software engineers, and domain experts to implement state-of-the-art machine learning solutions. Key Responsibilities: Model Development: Design, build, and maintain scalable machine learning models and algorithms.Data Analysis: Analyze and preprocess data from various sources to prepare it for model training.Model Training Evaluation: Train, validate, and tune machine learning models to achieve optimal performance.Deployment: Deploy models into production and integrate them with existing systems.Monitoring Maintenance: Monitor model performance in production and update models as necessary to ensure they remain accurate and relevant.Collaboration: Work with cross-functional teams, including data scientists, software engineers, and product managers, to understand requirements and deliver solutions.Research: Stay current with the latest developments in machine learning and AI to continuously improve our technology stack.

公司介紹： 我們的客戶是一家領先的金融科技公司，致力於通過數位、數據和技術推動整體轉型。公司正在積極打造數據驅動文化，以成為提供卓越金融服務的科技公司為目標。公司環境開放創新，鼓勵員工發揮創造力，實現職業理想。 JD: 1. 機器學習、深度學習或統計分析模型專案開發 2. 配合數據技術發展目標，研究與實作可落地應用之新興數據模型技術 3. 協助數據轉型，規劃end-to-end的數據應用解決方案 4. 當負責之數據服務被設定為""不能中斷""之服務等級，則需配合維運團隊於非上班時段on call以便即時處理問題，確保服務穩定。

This role requires you to work in a shift pattern or non-standard work hours as required. This may include weekend work.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Pune, Maharashtra, India; Bengaluru, Karnataka, India.Minimum qualifications: Bachelor's degree in Computer Science, Engineering, Mathematics, a related technical field, or equivalent practical experience. 2 years of experience in a technical role such as technical support, software engineering, or solutions engineering. Experience coding in one or more general purpose languages (e.g., Python, Java, Go, C or C++) including data structures, algorithms. Experience with Artificial Intelligence (AI) concepts and Machine Learning (ML) techniques. Experience with computer networking (e.g., TCP/IP, DNS, load balancing, routing) and Linux/Unix system administration. Preferred qualifications: Professional-level certification on Google Cloud, such as the Professional Machine Learning Engineer or Professional Cloud Architect. Experience with Google Cloud's AI/ML product portfolio, including Vertex AI (Vertex AI Workbench, Pipelines, Endpoints, TensorBoard) and Generative AI tools (Gemini, Gen AI Studio). Experience in specialized ML areas like Natural Language Processing (NLP), Computer Vision, or Recommendation System. Experience with public cloud infrastructure and core services (e.g., Compute Engine, Cloud Storage, BigQuery). Knowledge of ML frameworks such as TensorFlow, Keras, or PyTorch. 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 Technical Solutions Engineer, you will own our large and important customer issues in addition to providing level two support to our other support teams. You will be a part of a global team that provides 24x7 support to help customers seamlessly make the switch to Google Cloud.In this role, you will troubleshoot technical problems for customers with a mix of debugging, networking, system administration, updating documentation, and when needed, coding/scripting. You will make our products easier to adopt and use by making improvements to the product, tools, processes and documentation. You will help drive the success of Google Cloud by understanding and advocating for our customers issues.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s 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 Troubleshoot and resolve technical issues across the Google Cloud AI/ML portfolio, focusing on customer-reported, deployment failures, model performance degradation and infrastructure-related problems. Work directly with customers on their ML deployments, including generative AI models to ensure production readiness and high availability. Utilize coding and scripting skills (primarily Python) to read, debug, and reproduce customer issues within their ML models (TensorFlow, PyTorch) or deployment environments (Kubernetes, Compute Engine). Manage customer problems through effective diagnosis, clear documentation and the development, implementation of new investigation tools to increase diagnostic speed. Develop an understanding of Google Cloud's AI/ML solutions and share this knowledge to upskill the wider global support organization. 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.

以「釋放製造業的潛力」為使命，致力於推動製造業的數據平台產品。 2022 年透過機器學習等多種技術，將製造業中極為重要的圖面數據進行結構化，並與各類資訊連結，讓圖面能夠作為資訊資產被靈活運用。該產品目前已被日本國內眾多大型製造商與加工公司廣泛採用，成長迅速。 自 2023 年起，我們也開始向海外市場拓展，包括美國、泰國、越南等地，加速推進全球佈局。 未來，我們將不只限於圖面資料，而是致力於透過科技手段，重現與整合製造業的專業知識，實現跨部門、跨企業的整體最適化。【工作內容】 MLOps 工程師將與機器學習工程師密切合作，負責建構、維護與營運能夠穩定提供機器學習與數據科學模型的系統基礎架構。此外，您也將引領建立數據收集管線，並推動數據資產活用。 以下為工作內容示例，實際工作項目不僅限於此，入職後的工作範疇將依據您的技術能力、專業知識與經驗共同討論決定： 建構支援機器學習模型推論的 API 與 Batch 運行環境，及使用 CI/CD 進行部署的系統架構 在正式環境中執行監控、效能調校等提升 Site Reliability 的相關開發 使用 Vertex AI 或 Argo Workflow 建立、維護與運營機器學習處理流程（Pipeline） 最佳化推論與訓練平台的成本效益 與建模人員、平台工程團隊進行有效溝通，並將相關流程進行文件化與制度化 ■ 使用語言 前端：TypeScript 後端：Rust、TypeScript、Python ■ 框架與函式庫 前端：React、Next.js、WebGL、WebAssembly 後端：Rust（axum）、Node.js（Express、Fastify、NestJS）、PyTorch ■ 基礎架構 Google Cloud、Google Kubernetes Engine（GKE）、Anthos Service Mesh ■ 資料庫／資料倉儲 CloudSQL（PostgreSQL）、AlloyDB、Firestore、BigQuery ■ API GraphQL、REST、gRPC ■ 監控與效能追蹤 Datadog、Sentry、Cloud Monitoring ■ 環境建置 Terraform ■ CI/CD GitHub Actions ■ 認證管理 Auth0 ■ 開發工具 GitHub、GitHub Copilot、Figma、Storybook ■ 團隊溝通工具 Slack、Discord、JIRA、Miro、Confluence

This role requires you to work in a shift pattern or non-standard work hours as required. This may include weekend work.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Bengaluru, Karnataka, India; Pune, Maharashtra, India.Minimum qualifications: Bachelor's degree in Computer Science, Engineering, Mathematics, a related technical field, or equivalent practical experience. 5 years of experience in a technical role such as Technical Support, Software Engineering, or Solutions Engineering. Experience coding in one or more general purpose languages (e.g., Python, Java, Go, C or C++) including data structures, algorithms, and software design. Experience with Artificial Intelligence (AI) concepts and Machine Learning (ML) techniques. Experience with computer networking (e.g., TCP/IP, DNS, Load Balancing, routing) and Linux/Unix system administration. Preferred qualifications: Professional-level certification on Google Cloud, such as the Professional Machine Learning Engineer or Professional Cloud Architect. Experience with Google Cloud's AI/ML product portfolio, including Vertex AI (Vertex AI Workbench, Pipelines, Endpoints, TensorBoard) and Generative AI tools (Gemini, Gen AI Studio). Experience in specialized ML areas like Natural Language Processing (NLP), Computer Vision, or Recommendation System. Experience with public cloud infrastructure and core services (e.g., Compute Engine, Cloud Storage,BigQuery). Knowledge of ML frameworks such as TensorFlow, Keras, or PyTorch. Ability to lead the design and implementation of AI-based solutions or debugging tools, demonstrating strong collaborating skills. 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. Our Technical Solutions Engineers lead and own our large and important customer issues in addition to providing level two support to our other support teams. You will be a part of a global team that provides 24x7 support to help customers seamlessly make the switch to Google Cloud.In this role, you will troubleshoot technical problems for customers with a mix of debugging, networking, system administration, updating documentation, and when needed, coding/scripting. You will make our products easier to adopt and use by making improvements to the product, tools, processes and documentation. Our Technical Solutions team is driven by customers and you will help drive the success of Google Cloud by understanding and advocating for our customers’ issues. 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 Troubleshoot and resolve highly technical issues across the Google Cloud AI/ML portfolio, focusing on customer-reported , deployment failures, model performance degradation and infrastructure-related problems. Work directly with customers on their ML deployments (including Generative AI models)to ensure production readiness,high availability. Utilize coding and scripting skills (primarily Python) to read,debug, and reproduce customer issues within their ML models (TensorFlow, PyTorch) or deployment environments(Kubernetes, Compute Engine). Manage customer problems through effective diagnosis,clear documentation and the development/implementation of new investigation tools to increase diagnostic speed. Develop an in-depth understanding of Google Cloud's AI/ML solutions and share this knowledge to upskill the wider global support organization. Participate in an on-call rotation, may include working non-standard hours,nights,or weekends as part of our global 24/7 support model. 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.

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。

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

我們正在尋找一位充滿熱情與創新精神的 AI 工程師，與我們攜手探索AI的前沿技術，打造創新解決方案，推動 AI 技術的落地與實踐。【你將負責的任務】研究與應用前沿技術* 深入研究前沿的 AI 深度學習技術，包括但不限於大型語言模型（LLM）、強化學習（RL）、模型微調（Fine-tuning）等。* 將最新研究成果轉化為實際解決方案，解決業務場景中的挑戰。AI 系統設計與開發* 使用主流 AI 框架（如 PyTorch、scikit-learn）設計並實現符合公司需求的 AI 功能。* 針對不同業務場景（如數據分析、電腦視覺等），開發專屬 AI 解決方案，並應用於技嘉硬體設備或內部系統（例如智慧客服）。技術趨勢追蹤與導入* 持續關注全球 AI 領域的最新技術與研究成果。* 快速評估、篩選並導入具潛力的解決方案。全流程 AI 產品開發* 參與從數據蒐集、特徵工程、模型設計、訓練到部署的完整產品開發流程。* 確保系統效能與穩定性，並負責 Prototype 的開發與驗證。跨部門協作與支持* 與工程師、PM、業務團隊緊密合作，確保 AI 產品成功落地與商業化。【你將獲得的機會】 技術挑戰與成長空間 * 面對並解決業界最前沿的技術難題，持續拓展你的專業技能。 * 豐富資源與專業培訓 提供業界領先的開發資源與充足的計算資源。 * 享有多元的學術交流與技術培訓機會。 開放與友善的工作環境 * 扁平化組織結構，溝通透明、鼓勵創新。 * 友善團隊氛圍，讓你的貢獻被充分肯定。 如果你熱愛 AI 技術，並希望走在技術的最前端歡迎加入我們！