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HOYA BIT 致力成為加密貨幣初學者的最佳信任夥伴，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。 ▏

Senior Data Scientist / Machine Learning Engineer Price Intelligence Demand Optimization 我們正在尋找一位兼具 數學能力、程式能力與商業思維 的 Senior Data Scientist / Machine Learning Engineer，負責打造一套從 0 到 1 的 Price Intelligence System。 這不是一個只停留在研究階段的模型開發職位。我們希望你能打造真正落地、可規模化、能驅動商業決策的演算法系統，協助企業在超過 50,000+ SKU 的商品組合中，進行大規模、自動化、即時化的價格決策。 你將參與一套由 15+ 個互相串接的模型 組成的 Price Intelligence Ensemble System，涵蓋需求預測、價格彈性、促銷成效、庫存優化、異常偵測與多目標最佳化等核心模組。 工作內容 1. 建立 Price Intelligence Ensemble System 你將參與設計並開發一套由多個模型組成的價格智慧系統，包括： Demand Forecasting 需求預測 Price Elasticity Modeling 價格彈性模型 Promotion Impact Modeling 促銷成效模型 Inventory Optimization 庫存最佳化 Meta-Learning / Ensemble Decision Engine Real-Time Anomaly Detection 即時異常偵測 你需要能夠理解模型之間的依賴關係、資料流、特徵工程、模型選擇、訓練流程與執行順序。 2. 開發 SKU-Level Demand / Pricing Models 你將建立能夠在 SKU 層級預測需求、庫存與價格反應的模型，並納入以下因素： Seasonality 季節性 Promotion Lift 促銷拉動效果 Macroeconomic Factors 總體經濟因素 Weather Patterns 天氣影響 Product Lifecycle 商品生命週期 Competitive Pricing 競爭價格 Inventory Velocity 庫存流速 相關模型可能包括： ARIMA / Prophet LightGBM / XGBoost Bayesian Models Hierarchical Models Causal Inference Models PyTorch-based models 3. 解決多目標最佳化問題 你將開發能夠平衡多個商業目標的最佳化模型，例如： Maximizing Revenue 提高營收 Maintaining Gross Margin 維持毛利 Clearing Seasonal Inventory 清理季節性庫存 Competitive Positioning 維持市場競爭力 Promotion Efficiency 提升促銷效率 你需要能夠將商業限制、價格防護條件、庫存壓力與營運規則整合進模型，形成可落地的價格決策引擎。 4. 建立即時異常偵測與促銷監控系統 你將開發 streaming / real-time models，監控促銷活動期間的實際銷售表現，並在銷售結果與預測落差過大時，提供即時決策訊號，例如： Deepen Promotion：加深折扣或擴大促銷 Throttle Promotion：降低促銷力度或停止活動 Inventory Risk Alert：庫存風險提醒 Margin Risk Alert：毛利風險提醒 5. 將模型部署到 Production Environment 你需要撰寫乾淨、可維護、可擴展的 Python 程式碼，並與工程團隊合作，將模型部署到 production pipeline。 技術環境包含： Python pandas / NumPy / scikit-learn PyTorch BigQuery Vertex AI Cloud Run AlloyDB Pub/Sub / Dataflow / Kafka SQL / PySpark Poetry 系統需要滿足即時或近即時的 latency 要求，例如 100ms 到 500ms。 必備條件 7 年以上 Data Scientist / Machine Learning Engineer 經驗 具備統計、數學、經濟、物理、運籌、工程或相關量化領域背景 熟悉 price elasticity estimation、demand curve modeling 或 demand forecasting 熟悉 time-series forecasting 方法，例如 ARIMA、Prophet、LightGBM、XGBoost 熟悉 Python 生態系，包括 pandas、NumPy、scikit-learn、PyTorch 具備進階 SQL 能力，能處理大型資料集與複雜分析查詢 理解 Bayesian methods、hierarchical models、causal inference 或 uncertainty quantification 有能力將模型從 research prototype 推進到 production pipeline 能與工程、產品、商業團隊溝通模型邏輯與商業影響 加分條件 有 e-commerce、retail、fashion retail、pricing 或 revenue management 經驗 有 price optimization、demand elasticity、markdown optimization 經驗 曾開發 multi-model ensemble system 或複雜 ML 系統 熟悉 GCP：BigQuery、Vertex AI、Cloud Run、Pub/Sub、Dataflow 熟悉 real-time ML / streaming architecture 有 apparel / fashion retail 商品生命週期、季節性促銷、庫存管理經驗 熟悉 competitive pricing intelligence、web scraping、price index monitoring、KVI strategy 有 SaaS product 或 internal pricing tool 開發經驗 具備 computer vision / apparel feature extraction 經驗 熟悉 PyTorch CNN architecture，能夠修改或訓練 vision models 我們希望你是這樣的人 你不只是會訓練模型，而是能夠理解模型如何真正影響商業結果。 你能夠在以下目標之間做出平衡： 營收 vs. 毛利 折扣深度 vs. 庫存去化 預測準確度 vs. 系統延遲 模型複雜度 vs. 可維護性 商業彈性 vs. 統計嚴謹性 你需要能夠向非技術主管清楚解釋，例如： 「為什麼這個 markdown depth 雖然折扣較深，但能在指定期間內最大化總毛利回收？」 適合你的原因 這個職位適合想要挑戰以下任務的人： 從 0 到 1 建立 Price Intelligence System 參與大規模 SKU pricing decision engine 的設計 將 machine learning、statistics、optimization 與真實商業場景結合 建立能實際影響營收、毛利與庫存決策的 production-grade ML system 與產品、工程、商業團隊共同打造可規模化的 AI pricing platform 技能關鍵字 Python、Machine Learning、Data Science、Price Optimization、Demand Forecasting、Price Elasticity、Time Series Forecasting、Bayesian Modeling、Causal Inference、PyTorch、LightGBM、XGBoost、BigQuery、Vertex AI、GCP、SQL、PySpark、Optimization、Retail Analytics、E-commerce、Inventory Optimization、Anomaly Detection、Computer Vision

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.

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.

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

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.

Google welcomes people with disabilities.Minimum qualifications: Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience. 3 years of experience in Python and a related machine learning package (e.g., Keras, PyTorch, HF Transformers). Experience in applied AI, with building systems around pre-trained models (e.g., prompt engineering, fine-tuning, Retrieval-Augmented Generation (RAG), orchestrating model interactions with external tools to deliver solutions). Experience with architecting, deploying, or managing solutions on a Cloud Platform (e.g., Google Cloud Platform). Ability to communicate in Japanese and English fluently to interact with internal and external stakeholders. Preferred qualifications: Master’s degree or PhD in AI, Computer Science, or a related technical field. Experience with implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s ADK) and patterns like ReAct, self-reflection, and hierarchical delegation. Knowledge of Large Language Model (LLM)-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing. About the jobIn this role, you will be an embedded builder who bridges the gap between frontier Artificial Intelligence (AI) products and production-grade reality within customers. You will manage blockers to production including solving the integration issues, data readiness issues, and state-management tests that prevent AI from reaching enterprise-grade maturity. You will be providing deployment of AI systems and act as a feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours.Responsibilities Serve as a developer for Artificial Intelligence (AI) applications, transitioning from prototypes to production-grade agentic workflows (e.g., multi-agent systems, Model Context Protocol (MCP) servers) that drive Return on Investment (ROI). Architect and code the connection between Google’s AI products and customer's live infrastructure, including Application Programming Interfaces (APIs), legacy data silos, and security perimeters as part of a team. Build evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety and latency. Identify repeatable field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams. Co-build with customer engineering teams to instill Google-grade development best practices, ensuring project success and end-user adoption. 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.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Bengaluru, Karnataka, India; Hyderabad, Telangana, India; Mumbai, Maharashtra, India.Minimum qualifications: Bachelor's degree in Computer Science or equivalent practical experience. 6 years of experience building machine learning solutions and working with technical customers. Experience designing cloud enterprise solutions and supporting customer projects. Experience coding in one or more general purpose languages (e.g., Python, Java, Go, C or C++) including data structures, algorithms, and software design. Preferred qualifications: Experience working with recommendation engines, data pipelines, or distributed machine learning. Experience with deep learning frameworks (e.g., Tensorflow, pyTorch, XGBoost). Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume). Understanding of the auxiliary practical concerns in production machine learning systems. About the jobThe Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners. As a Cloud AI Engineer, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI. You will work with customers to identify opportunities to apply machine learning in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. Additionally, you will work closely with Product Management and Product Engineering to build and constantly drive excellence in our products.In this role, you are the Google Engineer working with Google's largest and most ambitious Cloud customers. Together with the team you will support customer implementation of Google Cloud products through: architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more.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 Be a trusted technical advisor to customers and solve complex machine learning challenges. Coach customers on the practical challenges in machine learning systems: feature extraction and feature definition, data validation, monitoring, and management of features and models. Work with customers, partners, and Google Product teams to deliver tailored solutions into production. Create and deliver best practice recommendations, tutorials, blog articles, and sample code. Travel up to 30% for in-region for meetings, technical reviews, and onsite delivery activities. 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.