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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

Mô tả công việcBuild and training pipelines for Generative AIImplement, optimize with state-of-the-art computer vision modelsCollaborate with teams to integrate computer vision algorithms into larger AI systems and applications.Stay up-to-date with the latest advancements in computer vision research and apply them to enhance our AI projects.Yêu cầu công việcFinal year students or fresh graduates with GPA above 3.2/4 or 8.0/10;Education: Top students from Vietnamese universityEnglish: IELTS 6.0, TOEIC 800, or Cambridge C1 (Nice to have)Experience: Fresh graduates or candidates with less than 2 years of experience.Employment Type: Full-time.Proficiency in programming languages such as Python, C++, or similar, along with experience in deep learning frameworks (e.g., PyTorch).

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

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

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.

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.

Google welcomes people with disabilities.Minimum qualifications: Bachelor's degree or equivalent practical experience. 10 years of experience with cloud native architecture in a customer-facing or support role. Experience with frameworks for deep learning (e.g., PyTorch, Tensorflow, Jax, Ray, etc.), AI accelerators (e.g., TPUs, GPUs), model architectures (e.g., encoders, decoders, transformers), and using machine learning APIs. Experience with Machine Learning (ML) model development and deployment. Ability to communicate in Japanese and English fluently to engage with local and internal stakeholders. Preferred qualifications: Master's degree in Computer Science, Engineering, Mathematics, a related technical field, or equivalent practical experience. Experience in building machine learning solutions and leveraging machine learning architectures (e.g., deep learning, LSTM, convolutional networks). Experience in architecting and developing software or infrastructure for distributed systems. Experience in data and information management. Ability to learn, understand, and work with technologies, methodologies, and solutions in the cloud/IT technology space. About the jobWhen leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products. As a Customer Engineer, you will partner with technical Sales teams as a subject-matter-expert in Artificial Intelligence and Infrastructure Modernization to differentiate Google Cloud to our customers. You will help the customers and partners understand the power of Google Cloud, develop cloud solutions and architectures to solve their business issues, engage in proof-of-concepts, and troubleshoot any technical questions and roadblocks. You will use the expertise and presentation skills to engage with customers to understand their business and technical requirements, and present solutions on Google Cloud. You will use excellent technical, communication and organizational skills. You will partner with internal engineering stakeholders to improve products and build solutions, improving results when in production and identifying ways to multiply the impact of the team as a whole. You will be a part of a team of Googlers working in an environment of respect where we promote equal opportunities to succeed.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 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 partnering 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 implement a complete solution on Google Cloud. Travel to customer sites, conferences, and other related events as needed, acting 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.

Logitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way.The Team and Role:As an Audio ML Engineer on the Logitech Hardware Audio ML and DSP Product team, you will be instrumental in developing Embedded Audio ML models that create innovative audio experiences for our customers [ e.g. Speech/Audio enhancement] . This role offers a significant opportunity to contribute directly to the audio products we develop.The Audio ML Engineers key responsibilities include:Develop production-ready Audio ML models, leveraging multi-sensor data from the product.Ensure these models are deployed for efficient inference on resource-constrained platforms by employing optimization techniques, including Post-Training Quantization (PTQ), Quantization-Aware Training (QAT), pruning etc.Your Contribution:Be Yourself. Be Open. Stay Hungry and Humble. Collaborate. Challenge. Decide and just Do. Share our passion for Equality and the Environment. These are the behaviors and values you’ll need for success at Logitech. In this role you will:Develop and implement highly optimized Audio ML models for efficient deployment on resource-constrained embedded platforms (e.g., ARM, Tensilica DSP, RISC-V, NPUs).Utilize techniques like  quantization [PTQ and QAT], and pruning to ensure effective on-device inference.Architect, optimize, and improve algorithm performance in complex real-world audio environments.Propose and implement novel solutions to challenging technical problems.Collaborate with various product teams to guarantee a premium and seamless customer audio experience.Key Qualifications:For consideration, you must bring the following minimum skills and experiences to our team:Audio ML Expertise (3 Years): Hands-on experience across the entire Audio ML lifecycle, including model training, tuning, quantization (PTQ and QAT), and deployment to production.ML Framework Proficiency: Advanced skills in ML frameworks (e.g., TensorFlow, Keras,PyTorch) with a history of successfully shipping Production ready Audio ML models.Embedded Optimization: Demonstrated success in optimizing model inference performance specifically for resource-constrained embedded systems.Strong Programming Best Practices: Excellent programming skills in Python and C, coupled with experience in code optimization and adherence to rigorous software best practices.Audio Data Augmentation: Experience with audio data augmentation techniques, including the ability to design, implement, and evaluate custom augmentation pipelines.ML Stack Debugging: Proficiency in Linux-based compute environments and experience debugging common ML training stack issues (e.g., OOM issues, CUDA errors, library conflicts).Preferred Qualifications:Audio Quality Assessment: Proven experience in designing and executing both subjective and objective audio quality evaluation protocols, including familiarity with industry-standard audio measurement metrics.Audio Artifact Resolution: Demonstrated track record of effectively identifying and resolving audio artifacts within ML audio chains..Technical Leadership Communication: Excellent communication, documentation, and leadership abilities, particularly in cross-functional technical environments.Initiative Execution: Highly driven individual with a demonstrated ability to deliver results and lead technically, both independently and as a contributing team member.Education:Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, or a closely related field.Equivalent practical experience is considered; advanced degrees or continuing education in audio ML are highly valued.#LI-SL1Across Logitech we empower collaboration and foster play. We help teams collaborate/learn from anywhere, without compromising on productivity or continuity so it should be no surprise that most of our jobs are open to work from home from most locations. Our hybrid work model allows some employees to work remotely while others work on-premises. Within this structure, you may have teams or departments split between working remotely and working in-house.Logitech is an amazing place to work because it is full of authentic people who are inclusive by nature as well as by design. Being a global company, we value our diversity and celebrate all our differences. Don’t meet every single requirement? Not a problem. If you feel you are the right candidate for the opportunity, we strongly recommend that you apply. We want to meet you!We offer comprehensive and competitive benefits packages and working environments that are designed to be flexible and help you to care for yourself and your loved ones, now and in the future. We believe that good health means more than getting medical care when you need it. Logitech supports a culture that encourages individuals to achieve good physical, financial, emotional, intellectual and social wellbeing so we all can create, achieve and enjoy more and support our families. We can’t wait to tell you more about them being that there are too many to list here and they vary based on location.All qualified applicants will receive consideration for employment without regard to race, sex, age, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.If you require an accommodation to complete any part of the application process, are limited in the ability, are unable to access or use this online application process and need an alternative method for applying, you may contact us toll free at 1-510-713-4866 for assistance and we will get back to you as soon as possible.

Logitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way.The Team and Role:Logitech’s Technology Office defines and implements the company’s technology innovation strategy. The group aims to bring state-of-the-art technologies and capabilities to Logitech’s RD and business groups, and enable breakthrough innovations.The Technology Office hosts a team of world-class scientists and engineers with expertise in computer science, robotics, human-machine interaction, cognitive sciences, machine learning and artificial intelligence. The activities of the group, based at the EPFL Innovation Park, Lausanne (Switzerland), span spatial computing, biosensing, and immersive video solutions. We are looking for a talented AI/ML Engineer to join our explorations in Video AI at the edge, based on our own work and in collaboration with academic partners.  Your Contribution:Be Yourself. Be Open. Stay Hungry and Humble. Collaborate. Challenge. Decide and just Do. Share our passion for Equality and the Environment. These are the behaviors and values you’ll need for success at Logitech. In this role you will:Solve the challenges of Logitechs AI at the edge. Continuously assess the state of the art in the field.Contribute to the definition of the Technology Office’s exploration agenda, fostering breakthrough innovation. Be responsible for the entire model lifecycle: designing and training next-generation neural networks at scale, then mastering the optimization and porting techniques to deploy them on embedded systems. Be working with a multidisciplinary team.Champion best practices to turn cutting-edge research into robust and innovative solutions that define the future of human-machine interaction.Key Qualifications:For consideration, you must bring the following minimum skills and experiences to our team:Min. 7 years of relevant work and/or academic experience in algorithm development (signal processing and AI/ML) with an emphasis on live video.Hands-on experience in AI/ML techniques, incl. deep learning, computer vision, sensor fusion, and time series processing, from model architecture to model training, optimization (quantization, pruning,  knowledge distillation, etc.) and porting.Experience training and scaling large models on distributed computing clusters (e.g., AWS, GCP, or institutional HPC clusters).Working experience in data collection, generation, augmentation and governance.Relevant experience in Software development best practices and embedded systems (hardware and software) architectures.Ability to rapidly dive into new scientific fields, researching and applying state-of-the-art in specific applications under tight engineering constraints.Ability to collaborate in a team spanning research and development.Experience in scientific research and collaborations.Keen interest in human-machine interactions.Pragmatic, innovative, curious autonomousOrganized and good communication skills.Preferred Qualifications:Design, training, evaluation and optimization of deep neural networks, e.g. CNNs, RNNs, GANs, GNNs, transformers, etc. SLM and VLM are a plus. Knowledge of loss modeling, multimodal training, supervised, unsupervised and self-supervised learning. Deep learning framework such as PyTorch, Tensorflow and TinyML, as well as ONNX models representation.Familiarity with cloud computing platforms or HPC environments for large-scale model training.General purpose programming languages, including Python, C/C, C# and Java.SW development on embedded platforms such as ARM and embedded AI. SDLC is a plus.Authoring and peer review of scientific publications. EducationMSc in Robotics, Computer Science, Computational Sciences, Machine Learning, Data Science or related sciencesPhD in related fields is a plus.#LI-SL1Across Logitech we empower collaboration and foster play. We help teams collaborate/learn from anywhere, without compromising on productivity or continuity so it should be no surprise that most of our jobs are open to work from home from most locations. Our hybrid work model allows some employees to work remotely while others work on-premises. Within this structure, you may have teams or departments split between working remotely and working in-house.Logitech is an amazing place to work because it is full of authentic people who are inclusive by nature as well as by design. Being a global company, we value our diversity and celebrate all our differences. Don’t meet every single requirement? Not a problem. If you feel you are the right candidate for the opportunity, we strongly recommend that you apply. We want to meet you!We offer comprehensive and competitive benefits packages and working environments that are designed to be flexible and help you to care for yourself and your loved ones, now and in the future. We believe that good health means more than getting medical care when you need it. Logitech supports a culture that encourages individuals to achieve good physical, financial, emotional, intellectual and social wellbeing so we all can create, achieve and enjoy more and support our families. We can’t wait to tell you more about them being that there are too many to list here and they vary based on location.All qualified applicants will receive consideration for employment without regard to race, sex, age, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.If you require an accommodation to complete any part of the application process, are limited in the ability, are unable to access or use this online application process and need an alternative method for applying, you may contact us toll free at 1-510-713-4866 for assistance and we will get back to you as soon as possible.

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:学士号を取得していること（同等の実務経験でも可）。顧客対応担当またはサポート担当としてクラウド ネイティブなアーキテクチャに携わった 10 年以上の経験。ディープ ラーニング フレームワーク（PyTorch、TensorFlow、Jax、Ray など）、AI アクセラレータ（TPU、GPU など）、モデル アーキテクチャ（エンコーダ、デコーダ、トランスフォーマーなど）に携わった経験および ML API の使用経験。ML モデルの開発とデプロイに携わった経験。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、担当地域や社内の関係者と関係を構築できること。望ましい経験/スキル:コンピュータ サイエンス、エンジニアリング、数学、または関連する技術分野の修士号（同等の実務経験でも可）。ML ソリューションを構築し、ML アーキテクチャ（ディープ ラーニング、LSTM、畳み込みネットワークなど）を活用した経験。分散型システム用ソフトウェアまたはインフラストラクチャを設計および開発した経験。データと情報の管理に携わった経験。クラウドや IT テクノロジー分野の技術、方法論、ソリューションを習得し、実践で応用できる能力。この求人について業界をリードする企業に Google Cloud を選んでいただくことは、クラウド コンピューティングを世界に広めるうえで大きな一歩となります。Google Cloud プロダクトの導入を決断された教育機関、政府機関、一般企業のお客様に対しては、生産性、可動性、連携性を引き出せるよう支援する必要があります。カスタマー エンジニアは、お客様が最も必要とされているサービスを提供するポジションです。具体的には、セールス担当の Google 社員のサポート役として、お客様の抱える主要な技術的課題を解決していただきます。プロダクト マーケティング マネジメントやエンジニアリングのチームと連携して、業界の最新動向を把握し、Google Cloud プロダクトの機能強化に貢献してください。カスタマー エンジニアは、AI とインフラストラクチャ モダナイゼーション分野のエキスパートとして、テクニカル セールスチームと協力しながら、Google Cloud の差別化要因をお客様にアピールするポジションです。お客様やパートナーに Google Cloud の良さを理解していただけるよう尽力してください。また、お客様やパートナーのビジネス課題を解決できるクラウド ソリューションやアーキテクチャの開発、概念実証のほか、技術的な質問への対応や障害のトラブルシューティングも行っていただきます。専門知識とプレゼンテーション能力を活かしてお客様に働きかけ、お客様のビジネス要件と技術的要件を理解したうえで、Google Cloud を活用したソリューションを提案してください。優れた技術的スキル、コミュニケーション能力、業務遂行能力が求められます。エンジニアリング分野の社内関係者と連携して、プロダクトの改善やソリューションの構築を行うとともに、実装後は改善に取り組み、チーム全体の影響力拡大につながる方法を見つけ出すことも業務の一環です。メンバーが互いに尊重し合い、チャンスが平等に与えられる環境で、Google チームの一員として存分に活躍してください。Google Cloud は、あらゆる組織のビジネスと業界におけるデジタル トランスフォーメーションを加速させるとともに、Google の最先端テクノロジーを活用したエンタープライズ クラスのソリューションと、デベロッパーがよりサステナブルに構築を行えるようにするツールを提供しています。200 以上の国や地域のお客様が、成長を可能にし、最も重大なビジネス上の問題を解決するための信頼できるパートナーとして Google Cloud を採用しています。業務内容チームメンバーと協力して、ビジネス チャンスの発掘および評価、お客様の主な技術的課題の見極め、技術的障壁を取り除くための戦略策定を行う。AI / ML に関する専門知識を共有し、お客様を技術面からサポートする（技術支援、入札レスポンスの支援、プロダクトやソリューションのブリーフィング、概念実証など）。プロダクト マネジメント チームと直接連携して、お客様の Google Cloud 導入を効果的に促進できるようにソリューションの優先順位を設定する。Google Cloud プロダクトを実際に使用して、お客様やパートナーの環境で統合のデモンストレーションを行い、プロトタイプを構築する。Google Cloud のソリューションを実装するために必要となる統合戦略、エンタープライズ アーキテクチャ、プラットフォーム、アプリケーション インフラストラクチャに関する提案を行う。Google Cloud の推進者として、必要に応じてお客様のオフィスを訪問し、会議などの関連イベントに参加する。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.