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Google welcomes people with disabilities.Minimum qualifications: Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience. 2 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.

Google welcomes people with disabilities.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. 6 years of software/application development experience and working with technical customers. Experience coding in one or more general purpose languages (e.g., Python, Java, Go, C or C++) including machine learning, Large Language Models (LLMs), and software design. Experience designing cloud enterprise solutions and supporting customer projects to completion. Ability to communicate in Japanese and English fluently to support local customers in Japan. 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, Extract, Transform, Load (ETL)/Extract, Load, Transform (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. 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 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 Serve as a trusted technical advisor to customers and solve machine learning issues. Deliver modern software to Google’s customers, including creating and executing enterprise application transformation and migration strategies. Collaborate 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.

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

Google は、障がい者採用の取り組みを進めています。必要な条件/経験:科学、テクノロジー、工学、数学のいずれかの学士号を取得していること（同等の実務経験でも可）。Python および関連する ML パッケージ（Keras、PyTorch、HF Transformers など）に携わった 2 年以上の経験。AI 応用分野における、事前トレーニング済みモデルを中心としたシステム構築経験（プロンプト エンジニアリング、ファインチューニング、検索拡張生成（RAG）、AI モデルと外部ツールの連携制御によるソリューション提供など）。クラウド プラットフォーム（Google Cloud Platform など）でソリューションを設計、デプロイ、管理した経験。日本語と英語による優れたコミュニケーション能力を備え、社内外の関係者とスムーズに連絡を取り合えること。望ましい経験/スキル:AI、コンピュータ サイエンス、または関連する技術分野における修士号または博士号。マルチエージェント システムを、LangGraph、CrewAI、Google の ADK などのフレームワークと ReAct、自己分析、階層的委任などのパターンを使用して実装した経験。大規模言語モデル（LLM）ネイティブの指標（トークン/秒、リクエストあたりの費用など）および状態管理と詳細なトレースを最適化する手法に精通していること。この求人についてこの職種では、最先端の AI プロダクトとお客様の実際の本番環境グレードとのギャップを埋めるために、客先で構築に従事していただきます。AI がエンタープライズ グレードに成熟するのを妨げる統合やデータ準備の問題、状態管理テストを解決し、本番環境への移行を阻む要因を管理します。AI システムのデプロイを提供するほか、現場で得られた実際の分析情報を Google Cloud の将来のプロダクト ロードマップに反映させるフィードバック ループの役割も果たします。Google Cloud の市場開拓チームに加わり、世界中の企業向けに AI 革命をリードするチャンスです。基盤となるテクノロジーの創出と大規模な運用実績に裏打ちされた Google ブランドの信頼性が、あなたの活躍を後押しします。このチームは、最先端の Gemini モデルや包括的な Vertex AI プラットフォームなど、世界最高峰の AI ポートフォリオにより、ビジネス上の問題解決を支援します。Google の協力的な企業文化は、DeepMind のエンジニアと研究者に直接相談できる環境を整備し、お客様の課題解決できるよう後押しします。共に Google の使命を推進し、カスタマー サクセスを後押しして、クラウドの新時代を切り拓きましょう。この市場を動かすのはあなたです。業務内容AI アプリケーションのデベロッパーとして、投資収益率（ROI）を向上させる本番環境グレードのエージェント型ワークフロー（マルチエージェント システム、Model Context Protocol（MCP）サーバーなど）への、プロトタイプからの移行を主導する。チームの一員として、Google の AI プロダクトとお客様の現在のインフラストラクチャ（アプリケーション プログラミング インターフェース（API）、従来のデータサイロ、セキュリティ境界など）との間の接続を設計およびコーディングする。エージェント システムが精度、安全性、レイテンシの要件を確実に満たすように、評価パイプラインとオブザーバビリティ フレームワークを構築する。Google の AI スタックから、繰り返し現れるフィールドのパターンや課題を特定し、再利用可能なモジュールに変換するか、あるいはエンジニアリング チーム向けの正式なプロダクト機能リクエストにする。カスタマー エンジニアリング チームと共同で構築を行い、Google レベルの開発ベスト プラクティスを導入して、プロジェクトの成功とエンドユーザーによる導入を確実なものにする。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.