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Established in 1987 and headquartered in Taiwan, TSMC pioneered the pure-play foundry business model with an exclusive focus on manufacturing its customers’ products. As of 2024, TSMC serves more than 500 customers and manufactures over 11,000 products for high-performance computing, smartphones, the Internet of Things (IoT), automotive, and digital consumer electronics. It is the world’s largest provider of logic ICs, with an annual capacity of 16 million 12-inch equivalent wafers. TSMC operates fabs in Taiwan as well as manufacturing subsidiaries in Washington State, Japan and China, and the Company began construction on a specialty technology fab in Dresden, Germany, in 2024. In Arizona, TSMC is building three fabs, with the first starting 4nm production in 2025, the second by 2028, and the third by the end of the decade.Advanced Quality System Development (AQSD) is part of TSMC's Intelligent Manufacturing Center (IMC), responsible for three main directions: Use statistical methods and conditional monitoring to inspect fab control charts, providing early warning of abnormal product yields; offer a fab defense system settings comparison platform to check that machines meet the internal control anomaly conditions set by the engineering department.Develop online fab analysis platforms through Big Data, Machine Learning, and Deep Learning techniques for online yield/defect analysis to ensure the quality of wafers produced in the fab.Develop systems and provide logical operations to control and implement escape mechanisms for material batch changes, measurement stages, and inspection stages, ensuring quality and optimizing product sampling rules. Responsibilities: Apply machine learning/optimization algorithm to build up models for optimizing semiconductor production.Develop analysis and optimization methods to enhance product quality, increase tool productivity and improve people productivity.Design, develop and test prediction models with real applications in manufacturing.Build a flexible framework to speed up the development process of AI models, with a focus on Large Language Models (LLMs) serving.Turn exciting AI prototypes/ideas into products, leveraging LLMs and other advanced AI technologies.Develop next-generation AI backend systems related to large-scale real-time data access, collection, analytics and monitoring.Establish and maintain MLops processes and tools, including model deployment, monitoring, and automation.Continuously improve the quality of AI production systems, particularly those utilizing LLMs.

Established in 1987 and headquartered in Taiwan, TSMC pioneered the pure-play foundry business model with an exclusive focus on manufacturing its customers’ products. As of 2024, TSMC serves more than 500 customers and manufactures over 11,000 products for high-performance computing, smartphones, the Internet of Things (IoT), automotive, and digital consumer electronics. It is the world’s largest provider of logic ICs, with an annual capacity of 16 million 12-inch equivalent wafers. TSMC operates fabs in Taiwan as well as manufacturing subsidiaries in Washington State, Japan and China, and the Company began construction on a specialty technology fab in Dresden, Germany, in 2024. In Arizona, TSMC is building three fabs, with the first starting 4nm production in 2025, the second by 2028, and the third by the end of the decade. The Facility Computer Integrated Manufacturing Department (FDCIM) is part of the Intelligent Manufacturing Center (IMC) at TSMC. It is primarily responsible for the development and maintenance of the following products: Development and maintenance of manufacturing-related report products for wafer fabs.Development and maintenance of engineering-related report products for wafer fabs.Development and maintenance of digital operation system products for facility management.Development and maintenance of big data application system products for facility management.Development and maintenance of facility management AI and machine learning related algorithm development and application system products. Responsibilities: FDCIM also employs software engineering and modular development techniques, combined with high-performance database application technologies, to develop systematized software with a unified version control system that accommodates different time zones and languages globally.In addition to its regular software product development work, FDCIM is also engaged in the research and development of new technologies, including the application of DevOps, Microservices, MLOps, AIOps, and more. Develop and maintain AI/ML systems and algorithmsCollaborate with cross-functional teams to identify and solve business problems using AI/ML techniquesDesign and implement machine learning models and data pipelinesTest and validate AI models for accuracy, scalability, and efficiencyDeploy AI solutions to production environmentsStay up-to-date with the latest advancements in AI technologies and industry trendsWrite clean and efficient code using HTML, CSS, and JavaScriptOptimize web applications for speed and scalabilityTest and debug web applications across multiple browsers and devicesStay up-to-date with the latest front-end development trends and best practices

Minimum qualifications: Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience. 3 year of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume). Experience with database administration techniques or data engineering, and writing software in Java, C++, Python, Go, or JavaScript. Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams. Preferred qualifications: Experience working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments. Experience working with Big Data, information retrieval, data mining, or machine learning. Experience in building applications with modern web technologies (e.g., NoSQL, MongoDB, SparkML, TensorFlow). Experience architecting, developing software, or production-grade Big Data solutions in virtualized environments. About the jobAs a Data Engineer for the Analytics, Insights and Measurement (AIM) team, you will Help customers, grow their businesses through trusted analytics, insights and measurement that ensure user privacy.Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.Responsibilities Create and deliver recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring approach and messaging to varied levels of business and technical stakeholders. Design, develop, and maintain reliable data pipelines to collect, process, and store data from various data sources. Implement data quality checks and monitoring to ensure data accuracy and integrity. Collaborate with cross-functional teams (data science, engineering, product managers, sales and finance) to understand data requirements and deliver data solutions. Enhance data infrastructure for performance, efficiency to meet evolving business needs. 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.

At Google, we have a vision of empowerment and equitable opportunity for all Aboriginal and Torres Strait Islander peoples and commit to building reconciliation through Google’s technology, platforms and people and we welcome Indigenous applicants. Please see our Reconciliation Action Plan for more information.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sydney NSW, Australia; Melbourne VIC, Australia.Minimum qualifications: Bachelor's degree or equivalent practical experience. 10 years of experience in software engineering, software infrastructure engineering, security, big data and analytics, cloud computing, or cloud networking. Experience with infrastructure, storage, platforms and data, as well as the cloud market and customer buying behavior. Experience engaging with, and presenting to, technical stakeholders and executive leaders. Preferred qualifications: Experience in technical sales or consulting in cloud computing, data analytics, and big data. Experience with architecture design, implementing, tuning, schema design and query optimization of scalable and distributed systems. Experience with developing data warehousing, data lakes, batch/real-time event processing, streaming, data processing (ETL/ELT), data migrations, data visualization tools, and data governance on cloud native architectures. Understanding of customer requirements with the ability to break down requirements and design technical architectures. 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 Practice Customer Engineer (CE) with a specialty in Data Analytics, you will partner with Technical Sales teams to differentiate Google Cloud to our customers. You will serve as a technical expert responsible for accelerating technical wins and adoption of complex, specialized workloads. You will leverage your deep expertise in our most strategic product areas, in partnership with Platform CEs, to perform designing of data foundation architectures and develop MVPs (Minimum Viable Products) to promote new, highly specialized solutions to customers. You will solve analytics-centered customer issues and provide a critical feedback loop to unblock customers and influence product development. You will leverage excellent organizational, communication, and presentation skills, engaging with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud.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 Drive the technical win for complex workloads within data analytics to ensure rapid and successful adoption, primarily supporting the business cycle from use case identification, technical evaluation, and through customer ramp. Combine business strategies, development and prototyping to provide functional, customer-tailored solutions that secure buy-in from customer domain experts. Provide deep technical consultation to customers, acting as a technical advisor and building lasting customer relationships. Leverage learnings from customer engagements to contribute to reusable solutions and assets with the Go-to-Market team. Provide critical feedback from customer engagements to Product and Engineering teams to improve architectures and solutions. Work within product and engineering management systems to document, prioritize and drive resolution of customer feature requests and issues. 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.

MoMo is the market leader in mobile payments in Vietnam, driven by a commitment to enhancing the lives of Vietnamese citizens through technological innovation.Within the MoMo BigData AI department, we prioritize Smart, Efficient, and Excellent execution. We are currently undergoing a major transformation to build a new hybrid data platform spanning multiple cloud vendors (GCP AWS).We are seeking an experienced Data Engineer to help us architect this platform to optimize for both budget control and technological flexibility. You will play a pivotal role in shifting our mindset from "managing data" to creating valuable Data Products that empower our internal consumers.Mô tả công việcWith MoMo's AI-first mission, we are designing and building a self-serve data platform to empower both internal teams and external partners. This platform allocates resources based on users’ needs to support:Ingesting data from diverse sources — either in batch or streaming, using both pull and push mechanismsDeveloping and deploying resilient data pipelines across the data lake, data warehouse, and streaming systemsDelivering high-quality, derived datasets to downstream tools such as BI solutions (e.g., Apache Superset,Looker Data Studio), via multiple delivery methods including APIs, datasets, and streaming dataMonitoring data quality throughout all data pipelines in the platform to ensure high-quality data, resulting in better decision-making, accurate reporting, and reliable machine learning outputsTracking and optimising resource usage for efficiencyAdditionally, we are building Data Management Systems that enable the Data Governance team and data consumers to:Manage the full data lifecycle within the big data platformExplore the MoMo data ecosystem independentlyProvide a single source of truth with high data quality to downstream consumersTrack and manage infrastructure costs across major projects, teams, and departmentsYêu cầu công việcThe MindsetPassion for Data: You dream in SQL ("SELECT COUNT(SHEEP)...") and care deeply about data accuracy.Product Thinking: You view data as a product, focusing on the usability and reliability of what you deliver to stakeholders.The Tech StackStrong Coding Skills: Proficiency in Java/Kotlin (for robust backend services) and Python (for data processing/scripting).Hybrid Cloud Infrastructure: Hands-on experience with GCP. Proficiency in Kubernetes, Docker, and IaC tools like Pulumi or Terraform.Big Data Engines: Deep understanding of computing engines like Spark, Trino, BigQuery, and Clickhouse.Orchestration: Experience building DAGs and workflows in Airflow or Temporal.Data Sources: Familiarity with diverse sources including App Events, CDC from transactional DBs (Oracle, MySQL, MSSQL), and streaming systems (Kafka, PubSub).Soft SkillsStrong problem-solving abilities with a focus on root-cause analysis.Collaborative spirit: You can explain complex infrastructure decisions to non-technical stakeholders.

Minimum qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience in product management or related technical role. 3 years of experience taking technical products from conception to launch (e.g., ideation to execution, 0 to 1, etc). Experience developing or launching products or technologies within databases, analytics, big data, or a related area. Experience in Apache Spark for data processing. Preferred qualifications: Experience driving product goal, go-to-market strategy, and design discussions. Experience working on developer tools or open source projects. Experience with data analytics tools (Hadoop, Spark), project involvement, and committership. Ability to drive results in collaborative, cross-functional environments with minimal oversight. About the jobAt Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day. In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users. In this role, you will be responsible for Google Cloud Platform (GCP) Data Analytics' big data analytics portfolio for Spark and other open source components in Dataproc and Serverless Spark.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 Drive the new set of innovation and growth powering Open Source Analytics at scale on Google Cloud. Work closely with customers, field and partners to address unmet need. Partner with business development and GTM teams to build growth strategies. Partner with engineering, research and key stakeholder teams to align roadmap and Objectives and Key Results (OKRs). 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.

MoMo is the leading mobile payments provider in Vietnam, committed to improving the lives of every Vietnamese through technological innovation. As our business continues to expand, were looking for an experienced Data Engineer to join our Data Platform team.At MoMo, we emphasize smart, efficient, and excellent execution, with a strong focus on data quality. Our data platform delivers critical insights for:Business and app performance monitoringMachine learning products including recommendation systems, personalization, risk scoring, fraud detection, targeted promotions, and financial servicesWere also building a next-generation hybrid data platform across multiple cloud providers, giving us greater control over both cost and technologyMô tả công việcWith MoMo's AI-first mission, we are designing and building a self-serve data platform to empower both internal teams and external partners. This platform allocates resources based on users’ needs to support:Ingesting data from diverse sources — either in batch or streaming, using both pull and push mechanisms;Developing and deploying resilient data pipelines across the data lake, data warehouse, and streaming systems;Delivering high-quality, derived datasets to downstream tools such as BI solutions (e.g., Apache Superset, Google Data Studio), via multiple delivery methods including APIs, datasets, and streaming data;Monitoring data quality throughout all data pipelines in the platform to ensure high-quality data, resulting in better decision-making, accurate reporting, and reliable machine learning outputs;Tracking and optimising resource usage for efficiency;Additionally, we are building Data Management Systems that enable the Data Governance team and data consumers to:Manage the full data lifecycle within the big data platform;Explore the MoMo data ecosystem independently;Provide a single source of truth with high data quality to downstream consumers;Track and manage infrastructure costs across major projects, teams, and departments.Yêu cầu công việcBachelor’s degree in Computer Science, Engineering, or a related field;A problem solver with a strong sense of ownership and accountability — not just a task executor;5+ years of experience working as a Data Engineer and 1+ year of experience working as leader;Curious and committed to lifelong learning, with a passion for solving business problems through engineering, improving service quality and usability, and maintaining a strong customer focus;Strong foundation in computer science fundamentals, including data structures, algorithms, database systems, and data modelling techniques;Proficient in at least one of the following languages: SQL, Python, JVM-based languages;Experience with databases such as PostgreSQL, MySQL, ClickHouse, DuckDB, etc;Skilled in analysing, designing, implementing, and optimising Data Vault or Dimensional Modeling for performance and cost;Hands-on experience with infrastructure platforms — cloud-based (e.g., GCP, AWS) or on-premise — and container orchestration using Kubernetes;Experience with data storage and processing engines like Apache Spark, Apache Flink, and StarRocks;Experience with Google Cloud Platform or Amazon Web Services is a plus.

Google welcomes people with disabilities.Minimum qualifications: Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience. 5 years of experience with two or more of the following: Web Tech, Data/Big Data, Machine Learning, Systems Admin, Networking, Kubernetes. 5 years of experience reading or debugging code in one or more general purpose languages (e.g. Python, Java, Go, C or C++). Ability to communicate in Japanese and English fluently to communicate with external and internal stakeholders. Preferred qualifications: Experience with SQL database administration, open source software communities, cloud networking solutions, or distributed computing. Experience in data analytics, warehousing, Extract Transform and Load (ETL) development, data science, or other Big Data applications. Experience working with recommendation engines, data pipelines, or distributed machine learning. Experience working in distributed applications or micro-services in a cloud based environment (e.g., Docker, Kubernetes). Experience working in a fluid environment with cross-collaboration across functions. Knowledge of Web application development/deployment, HTTP/RESTful API troubleshooting, or database design/troubleshooting. 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 solve the technical issues to show how our products can make businesses more collaborative. You work 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 important in helping Google grow its cloud business and helping companies around the world innovate.Responsibilities Develop an understanding of Google Cloud's Data Analytics (e.g. BigQuery), AI/ML, and underlying architectures by troubleshooting, reproducing, and determining the root cause for customer reported issues, building tools, and diagnosis. Act as a consultant and subject-matter-expert for internal stakeholders in Engineering, Sales, and customer organizations to resolve technical deployment obstacles and improve Google Cloud. Work as a part of a team of Engineers/Consultants that globally ensure 24 hour customer support. This may include a need to sometimes work non-standard work hours or shifts. Understand customer issues, advocate for their needs with internal teams, including Product and Engineering teams, and drive production. Work with customers on their production deployment to resolve issues and achieve product readiness and availability. 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.

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.

Minimum qualifications: Bachelor's degree in Science, Technology, Engineering, or equivalent practical experience. 3 years of experience troubleshooting and advocating for customers' needs, triaging technical issues, or software development. Experience writing, reading, and debugging code in one of the following: Java, C, C++, Python, or Go. Experience with web technologies (e.g., HTTP, HTML, DNS, TCP). Ability to participate in on-call rotation, which may occur outside of standard working hours, including nights, weekends and holidays. Preferred qualifications: Experience administering and querying data in distributed, columnar or analytic oriented databases or distributed data processing frameworks. Experience with open source distributed storage and processing utilities in the apache hadoop family or workflow orchestration products. Experience in data analytics, warehousing, ETL development, data science or other big data applications. 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. The high touch support solutions engineers step in and own the large and important customer issues in addition to proactively helping improve customer experiences. 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 provide a high-touch, dedicated service to the most critical customers with complex environments, aiming to anticipate their needs, optimize product performance, and enable customer success across complex environments.The high touch support team’s focus on proactive solutions and customer-centric supportability helps avoid issues, build customer trust, enable customers' continuous growth and long term success on Google Cloud Platform (GCP). You will troubleshoot technical problems for customers through debugging, networking, system administration, updating documentation, and coding/scripting. You will make the products easier to adopt and use by making improvements to the product, tools, processes and documentation. 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 customers on their production deployments to resolve issues and achieve product readiness, availability, and scale. Triage and handle technical escalations, including platform outages, technical issues, and executive concerns. Develop an in-depth understanding of Google Cloud's product technology and architectures by troubleshooting, reproducing, and determining the root cause for customer-reported issues, build tools, and diagnosis. Act as consultant and subject matter expert for internal stakeholders in engineering, sales, customer organizations to resolve technical deployment obstacles and improve Google Cloud. Understand customer issues, advocate for their needs with internal teams, including Product and Engineering teams, to find ways to improve the product, and drive production. Work as part of a team that globally ensure 24-hour customer support. This will include a need to sometimes work non-standard work hours/shifts, and may include weekend work. 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.