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【職位概述】 Tricuss (十論科技) 致力於顛覆傳統研發流程（Revolutionize RD）。旗艦產品「企業級 Co-researcher AI Agent」為自主虛擬科學家，融合 Agentic AI、大數據與物理模擬，能自主設計假說、推演，並自動檢索論文與內部資料以加速研發探索。 我們將系統與「物理基礎數位孿生（Physics-based Digital Twins）」深度結合，專為地端（On-premise）與封閉網路（Air-gapped）高資安客戶打造，實現最高千倍加速並減少 70% 實體實驗。目前我們與 NVIDIA、Qualcomm、Intel 及世界頂尖半導體與 AI 伺服器供應鏈的客戶們密切合作，邀您共同定義下一代研發標準。 身為後端工程師，您將與創辦團隊及產品、AI 核心成員緊密協作，負責開發、實作並維護產品的後端服務與 API。我們是非常早期的團隊，您將直接參與真實 production 系統的建置與決策，從一開始就擁有自己負責的模組，並在快速迭代中累積系統設計、大數據與 AI 代理整合的實戰經驗。我們以實作能力與學習速度為主要評斷標準，不以年資數字設限。 【主要職責】 後端服務開發： 使用 Node.js 與 TypeScript 開發高效、穩定的後端服務與功能模組。撰寫具備高可讀性、高維護性的程式碼，穩健支撐持續增長的業務邏輯與資料處理需求。 API 設計與前後端協作： 設計並實作高效的 RESTful API，與前端工程師密切協作，確保系統功能無縫對接，並逐步參與與企業客戶內部系統及第三方工具的資料對接。 資料庫操作與效能優化： 負責 MongoDB 資料庫的結構設計與資料存取（使用 Mongoose），進行索引優化與慢查詢排查，確保資料讀寫的正確性與效能。 大數據與 AI 整合協作（核心成長方向）： 作為應用程式層與底層資料服務的橋樑，協助開發後端服務與 API，將前沿的 AI 代理技術整合進產品中——包含 RAG（檢索增強生成）檢索、向量資料庫，以及與 Hadoop、Apache Iceberg、Apache Spark 等大數據生態系的介接。 程式碼品質與效能突破： 撰寫單元測試 (Unit Testing)、積極參與程式碼審查 (Code Review)，定位並協助解決系統瓶頸與非同步阻塞，確保服務的高可用性與擴展性。 地端部署與容器化協作： 與 DevOps 團隊配合，了解應用程式的容器化配置 (Docker) 與地端部署流程，逐步熟悉封閉網路 (Air-gapped) 環境下的交付與橫向擴展實務。 === 【Position Overview】 Tricuss is on a mission to revolutionize RD. Our flagship enterprise-grade Co-researcher AI Agent is an autonomous virtual scientist fusing Agentic AI, big data, and physics simulation to formulate and reason through hypotheses, while automatically retrieving papers and internal data to accelerate RD. Deeply integrated with Physics-based Digital Twins and purpose-built for on-premise, air-gapped, high-security customers, it delivers up to 1000x acceleration and cuts physical experiments by 70%. We work closely with customers across NVIDIA, Qualcomm, Intel, and the world's leading semiconductor and AI server supply chains—join us in defining the next generation of RD standards. As a Backend Engineer, you'll work with the founding team and core product and AI members to develop and maintain the backend services and APIs powering our product. As a very early-stage team, you'll build and own real production modules from day one, gaining hands-on experience in system design, big data, and AI agent integration through rapid iteration. We evaluate on hands-on ability and learning speed—not years of experience. 【Key Responsibilities】 Backend Service Development: Build high-performance, reliable backend services and modules with Node.js and TypeScript. Write readable, maintainable code that robustly supports growing business logic and data-processing needs. API Design Front-End/Back-End Collaboration: Design and implement efficient RESTful APIs, working closely with front-end engineers for seamless integration, and gradually take on data integration with enterprise customers' internal systems and third-party tools. Database Operations Performance Optimization: Own MongoDB schema design and data access (via Mongoose), optimize indexes, troubleshoot slow queries, and ensure correct, performant reads and writes. Big Data AI Integration (Core Growth Track): Bridge the application layer and underlying data services, helping build backend services and APIs that integrate cutting-edge AI agent tech—including RAG (Retrieval-Augmented Generation), vector databases, and connections to big data ecosystems like Hadoop, Apache Iceberg, and Apache Spark. Code Quality Performance Breakthroughs: Write unit tests, actively join code reviews, and identify and help resolve system bottlenecks and async blocking to ensure high availability and scalability. On-Premise Deployment Containerization: Work with DevOps to learn application containerization (Docker) and on-premise deployment, progressively gaining hands-on familiarity with delivery and horizontal scaling in air-gapped environments.

【職位概述】 Tricuss (十論科技) 致力於顛覆傳統研發流程（Revolutionize RD）。旗艦產品「企業級 Co-researcher AI Agent」為自主虛擬科學家，融合 Agentic AI、大數據與物理模擬，能自主設計假說、推演，並自動檢索論文與內部資料以加速研發探索。 我們將系統與「物理基礎數位孿生（Physics-based Digital Twins）」深度結合，專為地端（On-premise）與封閉網路（Air-gapped）高資安客戶打造，實現最高千倍加速並減少 70% 實體實驗。目前我們與 NVIDIA、Qualcomm、Intel 及世界頂尖半導體與 AI 伺服器供應鏈的客戶們密切合作，邀您共同定義下一代研發標準。 身為 AI 工程師，您將是打造我們旗艦產品「企業級 Co-researcher AI Agent」的核心推手。我們的產品不僅僅是回答問題的聊天機器人，而是具備深度邏輯推理、自主實驗與數據探勘能力的虛擬資料科學家與研究夥伴。您的挑戰在於研發並優化結合大型語言模型 (LLM) 與傳統機器學習 (ML) 的複合型 AI 代理 (AI Agent)，使其能自主提出假設、設計實驗、操作 ML 模型，並與企業內部由 Hadoop、Apache Iceberg、Apache Spark 及 ETL 構建的大數據生態系進行深度交互。您必須確保這個強大的系統能在嚴格的合規標準與封閉網路下安全運行，為客戶產出具備極高商業與研發價值的洞察。 【主要職責】 Co-researcher AI 代理大腦開發： 設計並實作具備複雜研發任務拆解、長期記憶與跨領域邏輯推理能力的 Co-researcher 核心架構。確保 AI 代理能自主理解企業業務痛點，主動制定研究計畫、調用各類分析工具，並綜合歸納出具策略意義的洞察報告。 ML Agent 研發與自動化機器學習 (AutoML) 整合： 開發專注於機器學習任務的 ML Agent，使其能自主執行資料預處理、特徵工程 (Feature Engineering)、模型訓練、超參數調優與模型評估。將傳統 ML 框架（如 Scikit-learn, XGBoost, PyTorch）無縫封裝為 AI 代理可靈活調用的工具 (Tools/Skills)。 大數據生態系與 AI 管線深度結合： 與資料工程及後端團隊緊密合作，利用 ETL 與 Apache Spark 等工具建立自動化的資料萃取與清洗管線。確保 Co-researcher 與 ML Agent 能即時存取、分析並處理儲存於 Hadoop 與 Iceberg 中的海量結構化與非結構化企業級數據。 進階 AI 檢索系統與向量工程： 針對企業內部專有文獻、研究報告與海量日誌，設計並優化檢索系統。建置高效能的向量資料庫 (如 Milvus, Qdrant)，實作混合檢索、語意路由與重排序策略，為 Co-researcher 提供精準的知識檢索底層支援。 地端大語言模型 (LLM) 部署與推論優化： 針對無法連網的高資安地端環境，負責開源大語言模型的評估與私有化部署。利用 vLLM 等推論引擎進行模型量化與效能調優，確保 Co-researcher 在邊緣或地端伺服器上能維持極低的延遲與高吞吐量。 AI 與 ML 資訊安全防護實作： 將資安思維融入 AI 與 ML 模型開發的每個環節。實作企業級資料脫敏、個人機密資訊 (PII) 過濾機制，防範模型毒化 (Data Poisoning) 與提示詞注入 (Prompt Injection)，確保 AI 代理的所有研究行為與資料存取絕對符合企業權限規範 (RBAC) 與零信任架構。 === 【Position Overview】 Tricuss is on a mission to revolutionize RD. Our flagship enterprise-grade Co-researcher AI Agent is an autonomous virtual scientist fusing Agentic AI, big data, and physics simulation to formulate and reason through hypotheses on its own, while auto-retrieving papers and internal data to accelerate RD. Integrated with Physics-based Digital Twins and purpose-built for on-premise and air-gapped, high-security customers, it delivers up to 1000x acceleration and 70% fewer physical experiments. We work with NVIDIA, Qualcomm, Intel, and the world's top semiconductor and AI server supply chains—come help define the next generation of RD standards. As an AI Engineer, you'll drive this flagship product—not a chatbot, but a virtual data scientist with deep reasoning, autonomous experimentation, and data-mining skills. You'll build and optimize a hybrid AI Agent combining LLMs with traditional ML that autonomously proposes hypotheses, designs experiments, operates ML models, and interacts deeply with the enterprise big-data ecosystem (Hadoop, Apache Iceberg, Apache Spark, ETL)—running securely under strict compliance and air-gapped networks to produce high-value commercial and RD insights. 【Key Responsibilities】 Co-researcher Agent "Brain" Development: Build the core architecture for decomposing complex RD tasks, long-term memory, and cross-domain reasoning, so the Agent can grasp enterprise pain points, formulate research plans, invoke analytical tools, and synthesize strategic insight reports. ML Agent and AutoML Integration: Build an ML Agent that autonomously runs data preprocessing, feature engineering, model training, hyperparameter tuning, and evaluation, wrapping traditional ML frameworks (Scikit-learn, XGBoost, PyTorch) into tools/skills it can flexibly invoke. Big-Data Ecosystem and AI Pipeline Integration: Partner with data engineering and backend teams to build automated extraction and cleansing pipelines (ETL, Apache Spark), enabling the Co-researcher and ML Agent to access and process massive structured and unstructured data in Hadoop and Iceberg in real time. Advanced AI Retrieval and Vector Engineering: Design and optimize retrieval over proprietary literature, reports, and logs; build high-performance vector databases (Milvus, Qdrant) with hybrid retrieval, semantic routing, and re-ranking for precise knowledge retrieval. On-premise LLM Deployment and Inference Optimization: Evaluate and privately deploy open-source LLMs for offline, high-security environments, using engines such as vLLM for quantization and tuning to keep latency low and throughput high on edge or on-premise servers. AI and ML Security: Embed security into every stage of development—enterprise-grade data masking and PII filtering, defense against data poisoning and prompt injection—ensuring all Agent research and data access comply with enterprise permissions (RBAC) and zero-trust architecture.

IntroASML is one of the world’s leading manufacturers of semiconductor-chip-making equipment. A majority of the world’s microchips receive their critical lithographic patterning in machines made by ASML. In addition ASML produces metrology tools and advanced applications to analyze and optimizethe performance of the customer production process.Sector and department informationWithin ASML, the sector Development and Engineering (DE) is responsible for the specification, design, integration, qualification, and sustaining of all ASML products. Taking advantage of customer and manufacturing proximity, the DE Applications of the ASML Center of Excellence (ACE) is located in Linkou, TaiwanPosition in the OrganizationThe holder of the position reports to the Manager of ACE DE in BL AppsJob MissionParticipate in the development of our distributed data and compute platform infrastructure (on premise cloud solution). Be accurate, be precise and own the specification, design and implementation of features and fixes. Onboard, integrate and configure open source or other packages that support the development of semiconductor process tuning applications on the ASML platform.Take initiatives in reducing manual actions for install upgrade, resolve structural stability issues and design automated tests suites to qualify both design and system setup on customer site. Investigate solve issues, identify root cause, containment, corrective and preventive actions, and work with customer teams to support TSMC, Micron, Samsung, China and many others.Geographical WorkplaceACE (ASML Taiwan, Linkou). Travel to the customer sites or the development headquarters (HQ) in the Netherlands for on-the-job training may be needed as part of the assignmentJob DescriptionYou will be working in the virtual compute platform (VCP) and ensure the platform can host analytics applications with the uptime expectation of 4 nine’s (99.99%) in the semiconductor factories of our customers.The platform is currently developed based on Kubernetes and DC/OS and migration from DC/OS to Kubernetes is in-progress. We develop the platform aspects in our team. Scheduling of resources, containerization, fail-over and data collection from scanner and measurement devices inside the fab.Installations and upgrades are automated with Ansible and Python. Other technologies you may encounter are Spark for data processing, Kafka for notifications and high volume data ingestion. Hadoop and HBASE are used for data storage.Responsibilities of this role:Develop and deliver new, key features that have high customer impact and help improve the operation efficiency of customer teams (a.k.a. CS/MO)Support VCP go-lives and complex activities at customers such as DE on-site / on-duty, escalation handling and containment creationBridge DE teams in Netherlands and customer teams in the field to speed up issue handling and solve field issues directly in AsiaJoin VCP system qualification to fill customer IT gaps in system test and test automation to increase platform reliability and system resilienceEducational LevelA relevant BSc or MSc in the area of software engineering, computer science, information systems, IT or MISProfileSolid experience with Kubernetes, Python and AnsibleExperience with automatic testing and qualification, if can be part of CI/CD pipelineAffinity to dig deep into the details of issues, e.g. container orchestration, networking, configurationLinux expertise, administrator, extensive experience troubleshooting complex Linux issuesNetworking expertise, understand TCP/IP protocol, troubleshoot firewall config issues, etc.Understands RHEV and Virtual MachinesExperience with the following technologies is plus: event messaging, security, storage solutions (e.g., Hadoop), alert monitoring solutions and cloud technology (Azure, AWS or GCP)Personal SkillsEnjoy working with people and willingly face the challenges that come with human interactionsCollaborate behaviors: plan and align, manage stakeholders, adapt to changes, and drive for resultsAccountable and able to communicate professionally with SW/non-SW colleagues worldwideCustomer values and quality oriented. You strive to find the best ways or solutions for top resultsProblem solving. Proven ability to work independently in a team setting and a multi-site environmentPersonal values: taking initiative, growth mindset, continuous improvement and agile developmentFluent spoken and written English or willing to learn/developInclusion and diversityASML is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that inclusion and diversity is a driving force in the success of our company.Need to know more about applying for a job at ASML? Read our frequently asked questions.

【職位概述】 Tricuss (十論科技) 致力於顛覆傳統研發流程（Revolutionize RD）。旗艦產品「企業級 Co-researcher AI Agent」為自主虛擬科學家，融合 Agentic AI、大數據與物理模擬，能自主設計假說、推演，並自動檢索論文與內部資料以加速研發探索。 我們將系統與「物理基礎數位孿生（Physics-based Digital Twins）」深度結合，專為地端（On-premise）與封閉網路（Air-gapped）高資安客戶打造，實現最高千倍加速並減少 70% 實體實驗。目前我們與 NVIDIA、Qualcomm、Intel 及世界頂尖半導體與 AI 伺服器供應鏈的客戶們密切合作，邀您共同定義下一代研發標準。 身為資深後端工程師，您將主導企業級核心系統的架構設計與開發，專注於打造高併發、高可用且具備極致安全性的後端服務。我們的產品服務於高度重視資訊安全與資料隱私的企業客戶，因此您不僅需要精通 Node.js 與 TypeScript 的深層邏輯，更要能駕馭複雜的企業級地端 (On-premise) 部署環境與網路限制。 您將與產品、DevSecOps、資料工程 (Data Engineering) 及 AI 核心團隊深度協作。面對企業客戶龐雜的數據資產，您將負責把我們前沿的 AI 代理技術，無縫整合至由 Hadoop、Apache Iceberg、Apache Spark 與 ETL 建構的現代化大數據生態系中。您的目標是確保系統在嚴苛的企業合規標準與封閉網路下，依然能展現卓越的效能、數據吞吐量與擴展性。 【主要職責】 核心系統架構設計與開發： 使用 Node.js 與 TypeScript 從零到一設計、建置與重構企業級後端架構。確保程式碼具備高可讀性、高維護性，並能穩健支撐快速增長的業務邏輯與海量數據處理需求。 大數據生態系整合與管線協作： 作為應用程式層與底層資料湖 (Data Lake) 的關鍵橋樑。開發後端服務與 API 介接 Airbyte 進行自動化資料抽取與同步 (ETL/ELT)；與 Apache Spark 分散式運算引擎深度整合以觸發或調度資料處理任務；並針對儲存於 Hadoop 及 Apache Iceberg 格式的海量結構化/非結構化資料，設計高效率的檢索與互動機制。 進階 API 設計與系統對接： 規劃並實作高效的 RESTful API 與 GraphQL 介面。負責與企業客戶內部核心系統（如 ERP、CRM、傳統關聯式資料庫）以及各類第三方工具進行深度、穩定且高度安全的資料對接。 企業級資訊安全與合規防護： 將最高規格的安全防護機制深植於後端架構中。實作嚴謹的身份驗證與授權機制（如 OAuth 2.0, SAML, JWT, 企業級 RBAC），防範常見網路攻擊，並確保大數據交互與傳輸過程中的最高級別加密。 資料庫設計與效能調優： 針對複雜商業邏輯與高併發場景，進行資料庫（如 MongoDB）的結構設計、索引優化與慢查詢排查。靈活運用關聯/非關聯式資料庫與分散式快取機制（如 Redis）大幅提升系統整體吞吐量。 地端部署與容器化架構支援： 與 DevOps 團隊密切配合，優化應用程式的容器化配置 (Docker)。確保後端 API 與數據處理微服務能夠在封閉網路 (Air-gapped) 的地端 Kubernetes 叢集中平滑部署與快速橫向擴展。 系統監控與效能瓶頸突破： 導入進階的 Node.js 效能分析工具 (Profiling, Memory Leak Detection)。結合系統可觀測性指標，快速定位並解決線上高壓環境下的效能瓶頸、非同步阻塞，以及與大數據叢集互動時的網路或運算延遲問題。 程式碼品質控管與團隊技術指導： 制定並推動嚴格的程式碼審查 (Code Review) 規範、單元測試 (Unit Testing) 與自動化整合測試標準。擔任團隊技術導師，提升工程團隊整體的技術底蘊與交付品質。 === 【Position Overview】 Tricuss is on a mission to revolutionize RD. Our flagship enterprise-grade Co-researcher AI Agent is an autonomous virtual scientist fusing Agentic AI, big data, and physics simulation to formulate and reason through hypotheses on its own, while automatically retrieving papers and internal data to speed RD exploration. We deeply integrate the system with Physics-based Digital Twins, purpose-built for on-premise and air-gapped, high-security customers—delivering up to 1000x acceleration and cutting physical experiments by 70%. We work closely with customers across NVIDIA, Qualcomm, Intel, and the world's leading semiconductor and AI server supply chains—join us in defining the next generation of RD standards. As a Senior Backend Engineer, you will lead the architecture, design, and development of our enterprise-grade core systems, building backend services that are highly concurrent, highly available, and exceptionally secure. Since our customers demand the highest information security and data privacy, you need deep mastery of Node.js and TypeScript internals plus the ability to navigate complex enterprise on-premise deployments and network constraints. You will collaborate closely with our Product, DevSecOps, Data Engineering, and core AI teams. Working with customers' vast, complex data assets, you will seamlessly integrate our cutting-edge AI agent technology into a modern big-data ecosystem built on Hadoop, Apache Iceberg, Apache Spark, and ETL pipelines—ensuring outstanding performance, data throughput, and scalability even under strict enterprise compliance and air-gapped networks. 【Key Responsibilities】 Core System Architecture, Design Development: Design, build, and refactor enterprise-grade backend architectures from scratch in Node.js and TypeScript. Keep the codebase highly readable and maintainable, robustly supporting fast-growing business logic and massive-scale data processing. Big-Data Ecosystem Integration Pipeline Collaboration: Bridge the application layer and the underlying data lake. Build backend services and APIs interfacing with Airbyte for automated extraction and sync (ETL/ELT); integrate deeply with the Apache Spark distributed engine to trigger and orchestrate jobs; and design high-efficiency retrieval and interaction for massive structured/unstructured data in Hadoop and Apache Iceberg formats. Advanced API Design System Integration: Plan and implement high-performance RESTful API and GraphQL interfaces. Own deep, stable, highly secure data integration with customers' core internal systems (ERP, CRM, legacy relational databases) and diverse third-party tools. Enterprise-Grade Security Compliance: Embed top-tier security deep within the backend architecture. Implement rigorous authentication and authorization (OAuth 2.0, SAML, JWT, enterprise-grade RBAC), defend against common cyberattacks, and ensure top-level encryption across all big-data interactions and transmission. Database Design Performance Tuning: Handle schema design, index optimization, and slow-query diagnosis for databases (e.g., MongoDB) under complex business logic and high concurrency. Leverage relational and non-relational databases plus distributed caching (e.g., Redis) to dramatically boost throughput. On-Premise Deployment Containerization Support: Partner with DevOps to optimize containerization (Docker). Ensure backend APIs and data-processing microservices deploy smoothly and scale out rapidly within air-gapped, on-premise Kubernetes clusters. System Monitoring Performance Bottleneck Resolution: Apply advanced Node.js performance tools (Profiling, Memory Leak Detection) with observability metrics to rapidly find and fix bottlenecks, async blocking, and network/compute latency under high load and big-data cluster interactions. Code Quality Control Technical Mentorship: Define and champion rigorous code review, unit testing, and automated integration testing standards. Mentor the team, raising its overall technical depth and delivery quality.

【職位概述】 Tricuss (十論科技) 致力於顛覆傳統研發流程（Revolutionize RD）。旗艦產品「企業級 Co-researcher AI Agent」為自主虛擬科學家，融合 Agentic AI、大數據與物理模擬，能自主設計假說、推演，並自動檢索論文與內部資料以加速研發探索。 我們將系統與「物理基礎數位孿生（Physics-based Digital Twins）」深度結合，專為地端（On-premise）與封閉網路（Air-gapped）高資安客戶打造，實現最高千倍加速並減少 70% 實體實驗。目前我們與 NVIDIA、Qualcomm、Intel 及世界頂尖半導體與 AI 伺服器供應鏈的客戶們密切合作，邀您共同定義下一代研發標準。 身為資深全端工程師，您將端到端（end-to-end）主導產品關鍵功能的設計與交付——從 React + TypeScript 的資料密集前端介面，一路打通到 Node.js + TypeScript 的企業級後端服務與大數據生態系整合。您不只是同時會寫前後端，更要能跨越整條技術棧做架構決策：定義前後端資料介面契約、權衡渲染與運算該落在哪一層、確保系統在嚴苛的企業合規標準與封閉網路下依然展現卓越效能與安全性。 我們的使用者是嚴謹、精準的半導體與材料科學家，他們要的不是花俏介面，而是能可靠呈現海量製程資料、複雜模擬結果與研究洞察的工具。您將與產品、設計、DevSecOps、資料工程 (Data Engineering) 及 AI 核心團隊深度協作，把前沿 AI 代理技術無縫整合至由 Hadoop、Apache Iceberg、Apache Spark 與 ETL 建構的現代化大數據生態系中，並擔任團隊的技術支柱與導師。 【主要職責】 端到端功能設計與交付： 從前端介面到後端服務，獨立負責產品關鍵功能的完整生命週期。使用 TypeScript 貫穿前後端，設計清晰的資料介面契約，確保端到端體驗的完整、穩定與高效能。 資料密集前端開發： 使用 React.js + Next.js（含 App Router、SSR / SSG）開發與擴展多個產品介面——內部管理後台、客戶端 Web App、AI 代理工作流介面與報告生成模組。針對大型表格（可達數千列）、複雜過濾排序、即時資料串流等場景，運用虛擬化（virtualization）、memoization、bundle size 分析與 React Profiler 持續優化渲染效能。 企業級後端架構與開發： 使用 Node.js 與 TypeScript 設計、建置與重構企業級後端服務與 API。規劃高效的 RESTful API 與 GraphQL 介面，確保程式碼具備高可讀性、高維護性，並能穩健支撐快速增長的業務邏輯與海量數據處理需求。 大數據生態系與 AI 整合： 作為應用程式層與底層資料湖 (Data Lake) 的關鍵橋樑，開發後端服務介接 RAG（檢索增強生成）檢索、向量資料庫，以及 Hadoop、Apache Iceberg、Apache Spark、Airbyte 等大數據生態系，將前沿 AI 代理技術整合進產品。 資料庫設計與效能調優： 針對複雜商業邏輯與高併發場景，進行資料庫（如 MongoDB）的結構設計、索引優化與慢查詢排查，靈活運用關聯/非關聯式資料庫與分散式快取（如 Redis）大幅提升系統吞吐量。 企業級資安與地端部署協作： 將嚴謹的身份驗證與授權機制（OAuth 2.0, SAML, JWT, 企業級 RBAC）深植於系統中；與 DevOps 團隊配合，優化容器化配置 (Docker)，確保前後端服務能在封閉網路 (Air-gapped) 的地端 Kubernetes 叢集中平滑部署與橫向擴展。 工程品質控管與技術指導： 制定並推動嚴格的程式碼審查 (Code Review)、單元測試 (Vitest / Jest / Testing Library) 與自動化整合測試標準。擔任團隊技術導師，沉澱前後端最佳實踐，提升整體技術底蘊與交付品質。 === 【Position Overview】 Tricuss is on a mission to revolutionize RD. Our flagship enterprise-grade Co-researcher AI Agent is an autonomous virtual scientist fusing Agentic AI, big data, and physics simulation to formulate and reason through hypotheses on its own, while automatically retrieving papers and internal data to speed RD exploration. We deeply integrate the system with Physics-based Digital Twins, purpose-built for on-premise and air-gapped, high-security customers—delivering up to 1000x acceleration and cutting physical experiments by 70%. We work closely with customers across NVIDIA, Qualcomm, Intel, and the world's leading semiconductor and AI server supply chains—join us in defining the next generation of RD standards. As a Senior Full-Stack Engineer, you will own the end-to-end design and delivery of key product features—from data-intensive React + TypeScript interfaces all the way through to enterprise-grade Node.js + TypeScript backend services and big-data integration. You won't just write both ends; you'll make architecture decisions across the whole stack: defining front-end/back-end interface contracts, deciding which layer rendering and computation belong in, and ensuring the system delivers outstanding performance and security even under strict enterprise compliance and air-gapped networks. Our users are rigorous semiconductor and materials scientists who don't want flashy UI—they want tools that reliably present massive process datasets, complex simulation results, and research insights. You'll collaborate closely with Product, Design, DevSecOps, Data Engineering, and core AI teams to seamlessly integrate cutting-edge AI agent technology into a modern big-data ecosystem built on Hadoop, Apache Iceberg, Apache Spark, and ETL—while serving as a technical anchor and mentor for the team. 【Key Responsibilities】 End-to-End Feature Design Delivery: Own the full lifecycle of key product features, from front-end interface to backend service. Use TypeScript across the stack, design clear data interface contracts, and ensure a complete, stable, high-performance end-to-end experience. Data-Intensive Front-End Development: Build and scale multiple interfaces in React.js + Next.js (App Router, SSR / SSG)—internal admin consoles, client-facing Web Apps, AI agent workflow UIs, and report generation. For large tables (up to thousands of rows), complex filtering/sorting, and real-time streaming, continuously optimize rendering via virtualization, memoization, bundle-size analysis, and the React Profiler. Enterprise-Grade Backend Architecture Development: Design, build, and refactor enterprise-grade backend services and APIs in Node.js and TypeScript. Plan high-performance RESTful API and GraphQL interfaces, keeping code highly readable and maintainable while robustly supporting fast-growing business logic and massive-scale data processing. Big-Data Ecosystem AI Integration: Bridge the application layer and the underlying data lake, building backend services that interface with RAG (Retrieval-Augmented Generation), vector databases, and big-data ecosystems such as Hadoop, Apache Iceberg, Apache Spark, and Airbyte to integrate cutting-edge AI agent technology into the product. Database Design Performance Tuning: Handle schema design, index optimization, and slow-query diagnosis for databases (e.g., MongoDB) under complex business logic and high concurrency, leveraging relational/non-relational databases and distributed caching (e.g., Redis) to dramatically boost throughput. Enterprise Security On-Premise Deployment: Embed rigorous authentication and authorization (OAuth 2.0, SAML, JWT, enterprise-grade RBAC) throughout the system. Partner with DevOps to optimize containerization (Docker), ensuring front-end and backend services deploy smoothly and scale out within air-gapped, on-premise Kubernetes clusters. Engineering Quality Control Technical Mentorship: Define and champion rigorous code review, unit testing (Vitest / Jest / Testing Library), and automated integration testing standards. Mentor the team, codify front-end and back-end best practices, and raise overall technical depth and delivery quality.

Astera Labs (NASDAQ: ALAB) provides rack-scale AI infrastructure through purpose-built connectivity solutions. By collaborating with hyperscalers and ecosystem partners, Astera Labs enables organizations to unlock the full potential of modern AI. Astera Labs’ Intelligent Connectivity Platform integrates CXL®, Ethernet, NVLink, PCIe®, and UALink™ semiconductor-based technologies with the company’s COSMOS software suite to unify diverse components into cohesive, flexible systems that deliver end-to-end scale-up, and scale-out connectivity. The company’s custom connectivity solutions business complements its standards-based portfolio, enabling customers to deploy tailored architectures to meet their unique infrastructure requirements. Discover more at www.asteralabs.com.Job Description Astera labs is seeking a skilled and motivated Data Scientist. This individual will play a pivotal role in identifying key data points for collection, developing strategies to accumulate data and deriving actionable insights an anomaly based on a solid foundation of relevant know-how. Also, will also be responsible for creating, testing, and deploying scripts and methods for data collection and analysis to support decision-making. The Engineer will collaborate with cross-functional teams to identify critical data sources to determine the most effective data collection strategies, will develop automated and scalable data collection pipelines, will ensure data quality, integrity, and consistency across all sources and may use AI techniques to refine the results toward failures predictions. Basic Qualifications Bachelor’s degree in computer science, Data Science, Engineering, Mathematics, or a related field. Advanced degrees in data science or Machine learning / AI - Advance. Proficiency in programming languages such as Python, R, or MATLAB. Strong understanding of data manipulation and analysis tools (e.g., Pandas, NumPy, SQL). Understanding of high speed interfaces such as Ethernet, PCI-E , WiFi. Experience with data visualization tools such as Tableau, Matplotlib, Graphana. Strong analytical and critical-thinking skills to identify patterns and outliers. Customer-obsession, Think and act with the customer in mind! Goal-driven, Self-motivated, be able to work independently and with teams with people around the globe. Entrepreneurial, open-minded behavior and can-do attitude. Required Experience Experience with data manipulation and analysis tools (e.g., Pandas, NumPy, SQL). Machine learning and AI techniques and frameworks (e.g., TensorFlow, Scikit-learn). Proven ability to manage multiple tasks and meet deadlines. Preferred Experience Embedded Firmware development with C-language, scripting with Python or other equivalent programming languages. Master’s degree in a relevant field. Experience with cloud platforms (e.g., AWS, Azure, GCP) for data storage and processing. Familiarity with big data technologies (e.g., Hadoop, Spark). Knowledge of engineering design tools and processes. We know that creativity and innovation happen more often when teams include diverse ideas, backgrounds, and experiences, and we actively encourage everyone with relevant experience to apply, including people of color, LGBTQ+ and non-binary people, veterans, parents, and individuals with disabilities.

MoMo is the market leader in mobile payments in Vietnam. We strive to make all transactions fast, easy and joyful. We are looking for an experienced Software Engineer to join our growing Big Data AI team. At MoMo, we make AI/Machine Learning the core component to almost every part of the product - product recommendation, personalization, conversational AI, eKYC, risk scoring, fraud detection, promotion targeting and financial services.As a Software Engineer specializing in Enterprise Applications, you will play a pivotal role in crafting and deploying advanced business solutions. This position offers a unique chance to make a significant impact by leveraging Enterprise Applications and scalable systems to transform business operations for millions of users. Join us in pushing the boundaries of enterprise technology and shaping the future of mobile payments in Vietnam.Mô tả công việcDevelop and Implement Enterprise Application Solutions: Design, build, and maintain advanced enterprise systems that enhance business operations, utilizing cutting-edge technologies and scalable architectures.Analyze and Critique Product Requirements: Evaluate and provide feedback on product requirements to ensure feasibility and alignment with technical capabilities.Contribute to System Architecture: Participate in the design and architecture of systems and infrastructure, ensuring robustness and scalability.Maintain High Standards of Code Quality: Write clean, maintainable, and efficient code in Kotlin and Python, and participate in code reviews to uphold the team's quality standards.Collaborate with Cross-Functional Teams: Work closely with product managers, data scientists, and other engineering teams to integrate enterprise-driven features into our platform, ensuring seamless user experiences.Mentor and Guide Team Members: Share your expertise with less experienced team members, fostering a culture of continuous learning and development within the team.Yêu cầu công việcStrong Problem-Solving Skills: You have a proven track record of tackling complex technical challenges and delivering effective solutions, particularly in the realm of AI and machine learning.Ownership and Proactivity: You take initiative and are driven to see projects through from start to finish. You are someone who can be relied upon to deliver results with minimal supervision.Backend Engineering Proficiency: Minimum 5 years of experience as a Software Engineer, with strong skills in backend languages like Kotlin, Python, Java, or Go.Big Data Technologies Expertise: Hands-on experience with distributed systems and big data technologies including Apache Kafka for real-time data streaming, Hadoop ecosystem (HDFS, MapReduce, Hive, Spark), and data processing frameworks. Experience with data warehousing solutions like Apache Airflow, Elasticsearch, and cloud-based big data platforms (AWS EMR, Google Cloud Dataflow, or Azure HDInsight) is highly valued.High Standards for Quality: You take pride in your work and strive to deliver solutions that are not only functional but also maintainable and scalable.Innovative and Forward-Thinking: You are passionate about exploring new technologies and finding ways to apply them to improve user experiences and business processes.Collaborative and Communicative: You work well in a team environment and can communicate effectively with technical and non-technical stakeholders alike.

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.Minimum qualifications: Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience. 3 years of experience in developing and troubleshooting data processing algorithms and softwares using Python, Java, Scala, Spark and hadoop frameworks. Experience working with one or more public cloud providers (e.g., Google Cloud Platform). Ability to travel up to 30% as required. Preferred qualifications: Experience in working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT and reporting/analytic tools, environments, and data structures. Experience in Big Data, information retrieval, data mining, or machine learning. Experience in building multi-tier, high availability applications with modern technologies such as NoSQL, MongoDB and SparkML. Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments. Experience with IaC and CICD tools like Terraform, Ansible, Jenkins etc. About the job As a Cloud Data Engineer, you will guide customers on how to ingest, store, process, analyze, and explore/visualize data on the Google Cloud Platform. You will work on data migrations and modernization projects, and with customers to design data processing systems, develop data pipelines optimized for scaling, and troubleshoot potential platform/product challenges. You will have knowledge of data governance and security controls. You will travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. Additionally, you'll work closely with Product Management and Product Engineering teams to build and constantly drive excellence in our products.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 Interact with stakeholders to translate complex customer requirements into recommendations for appropriate solution architectures and advisory services. Engage with technical leads, and partners to lead high velocity migration and modernization to GCP. Design, migrate/build, and operationalize data storage and processing infrastructure using cloud native products. Design and implement data migration strategies for various database types (e.g., PostgreSQL, Oracle, Alloy DB, etc.). Develop and implement data quality and governance procedures to ensure the accuracy and reliability of data. Create communication strategies, risk and issue management, status reports, project matrix, and track timelines. Take various project requirements and organize them into clear goals and objectives, and create a work breakdown structure to manage internal and external stakeholders. 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. 5 years of experience in a client facing, technical consulting, or technical support role. Experience with cloud data migration. Ability to communicate in Japanese and English fluently to interact with internal and external stakeholders. Preferred qualifications: MBA or Master's degree in Computer Science, or a related engineering field. 7 years of experience in technical client services. Experience designing and deploying large-scale distributed data processing systems with one or more technologies such as SQL server, MySQL, PostgreSQL, MongoDB, Cassandra, Redis, Hadoop, Spark, HBase, Vertica, Netezza, Teradata, Tableau, or MicroStrategy. Experience with reading software code in one or more languages such as Java, JavaScript, Python. Knowledge of AI/ML and Generative AI. Excellent communication, presentation, and problem-solving 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. As a Cloud Consultant for Big Data and Analytics, you will work with customers on critical projects to help them transform their businesses. You will provide management, consulting, and technical capabilities to customer engagements while working with customer executives and key technical leaders to deploy solutions via Google Cloud Platform. You will also work with key partners, serving accounts to manage programs, deliver consulting services, and provide technical guidance and best practice expertise.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 Manage and deliver successful implementations of cloud solutions, in collaboration with customer's technical leads, client executives, and partners. Act as a trusted advisor to decision makers throughout the engagement. Propose solution architectures and manage the deployment of cloud based data and analytics solutions, according to complex customer requirements and implementation best practices. Advocate for customer needs in order to overcome adoption blockers and drive new feature development based on your field experience. Interact with sales, partners, and customer technical stakeholders to manage project scope, priorities, deliverables, risks or issues, and timelines for successful client outcomes. Work with internal specialists, Product, and Engineering teams to package best practices and lessons learned into thought leadership, methodologies, and published assets. 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. 7 years of experience in a client facing, technical consulting, or technical support role. Experience with cloud data migration. Preferred qualifications: MBA or Master's degree in Computer Science, or a related engineering field. 10 years of experience in technical client services. Experience designing and deploying large -scale distributed data processing systems with one or more technologies such as SQL server, MySQL, PostgreSQL, MongoDB, Cassandra, Redis, Hadoop, Spark, HBase, Vertica, Netezza, Teradata, Tableau, or MicroStrategy. Experience with reading software code in one or more languages such as Java, JavaScript, Python. Knowledge of AI/ML, Generative AI. Excellent communication, presentation, and problem-solving 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. As a Cloud Consultant for Big Data and Analytics, you will work with customers on critical projects to help them transform their businesses. You will provide management, consulting, and technical capabilities to customer engagements while working with customer executives and key technical leaders to deploy solutions via Google Cloud Platform. You will also work with key partners, serving accounts to manage programs, deliver consulting services, and provide technical guidance and best practice expertise.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 Manage and deliver successful implementations of cloud solutions, in collaboration with customer technical leads, client executives, and partners. Act as a trusted advisor to decision makers throughout the engagement. Propose solution architectures and manage the deployment of cloud based data and analytics solutions, according to complex customer requirements and implementation best practices. Advocate for customer needs in order to overcome adoption blockers and drive new feature development based on your field experience. Interact with sales, partners, and customer technical stakeholders to manage project scope, priorities, deliverables, risks or issues, and timelines for successful client outcomes. Work with internal specialists, Product, and Engineering teams to package best practices and lessons learned into thought leadership, methodologies, and published assets. 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.