Cake Job Search

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

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.

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 or equivalent practical experience. 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree. 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). 1 year of experience with core GenAI concepts (LLM, Multi-Modal, Large Vision Models). Experience with text, image, video, or audio generation. Preferred qualifications: Master’s degree. 5 years of experience in software development or ML. 3 years of experience testing, maintaining or launching software products, and 1 year of experience with software design and architecture or experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models), GenAI-related concepts (language modeling, computer vision), ML algorithms and tools (e.g. TensorFlow), or NLP. 2 years of experience with data structures and algorithms. Experience in Machine Learning, Machine Learning Infrastructure, AI Platform, Python, C++. About the jobGoogle's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. 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 Lead end-to-end features from front-end, client, serving and modeling, as well as collaborating across multiple teams and functions within editors as well as GDM, to bring model capabilities to the AI features. 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 in Computer Science, Mathematics, a related field, or equivalent practical experience. 1 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, as well as 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 multi-tier high availability applications with modern web technologies (e.g., NoSQL, MongoDB, SparkML, TensorFlow). Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments. About the jobAs a Data Engineer for the Enterprise Platforms team, you will play a vital role in building and maintaining the data infrastructure that fuels our product strategy. You will design, develop, and optimize data pipelines, ensuring data quality and accessibility for advanced analytics. Your technical expertise will enable the product team to leverage data-driven insights to optimize product feature adoption and performance and measure the impact of strategic initiatives. To accelerate the growth and market leadership of Enterprise Buying Platforms (DV360 and SA360), you will answer critical business questions and deliver actionable, data-driven insights that inform product and commercial strategy. The Enterprise Platform Data Science team provides quantitative support, market understanding and a strategic perspective to our partners throughout the organization, in close collaboration with the Ads Commerce Finance team.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 best practice 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 scalable and reliable data pipelines to collect, process, and store data from various data sources. Implement robust 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 impactful data solutions. Optimize data infrastructure for performance, efficiency, and scalability 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.

Google welcomes people with disabilities.Minimum qualifications: Bachelor’s degree or equivalent practical experience. 5 years of experience with software development in programming languages such as C++, Python, Kotlin, Typescript, TensorFlow, Jax for image processing and automation tasks. 3 years of experience in Image Signal Processor (ISP) processing, Android application, desktop program, Machine Learning (ML) application, web based app development. Preferred qualifications: Master's degree or PhD in Electrical Engineering, Computer Science, Image Processing, Machine Learning, or a related field. 8 years of experience in image processing algorithms, with significant contributions to mobile camera application development, camera or video related Android application development. Familiarity with the end-to-end product development lifecycle for mobile phones, particularly concerning camera features. Familiarity with the AI application integration and ML model fine tune and optimization. About the jobGoogle's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. In this role, you will bridge the gap between model research and end-user application. You will not only fine tune models for our specific domain but also build the actual web and mobile interfaces. You will work with teams to establish the AI pipeline from data curation to edge deployment, creating immersive camera based experiences that provide real-time instructions and feedback.Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.Responsibilities Build responsive web apps and mobile apps to host the AI models, and develop a video analysis viewer that allows side-by-side comparison of input video vs processed output to visualize model performance. Design and implement the interaction I/O interface, ensuring intuitive user inputs and clear, actionable AI outputs. Implement real time inference loops or on-device mobile inference engines and develop live instruction indicators using Augmented Reality (AR) style overlays and visual guides to direct users on live camera feeds. Manage camera lifecycle management to ensure smooth frame capture and processing without draining battery or freezing the UI. Modify foundation models specifically for multimedia use cases and optimize models for edge deployment (quantization, pruning, distillation) to ensure low latency on mobile devices and web browsers. 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.

To start the application process, you will need an updated CV or resume and a current unofficial or official transcript in English. Click on the “Apply” button on this page and provide the required materials in the appropriate sections (PDFs preferred):In the “Resume Section:” attach an updated CV or resume. Please ensure you include the following in it, all consolidated in a single PDF:Research work: Projects, Publications, Research experience and References (if any)Statement of purpose (no more than 500 words), detailing reasons for your interest in the Post-Doctoral Researcher role. Please ensure you’ve listed your graduation date (in MM/YY) In the “Education Section:” attach a current or recent unofficial or official transcript in English. Under “Degree Status,” select “Now attending/Graduated” to upload a transcript.If you think this role interests you, please apply to this role.Minimum qualifications: PhD degree in a STEM field (e.g., Computer Science, Mathematics, or Statistics) or equivalent practical experience. Experience with one or more general purpose programming languages: Python, C/C++, or Java, etc. and training deep learning models in frameworks such as JAX, TensorFlow, or PyTorch. Research experience in machine learning or AI techniques (e.g., open source project(s), campus lab experience, research internship(s), or publication(s)). One or more scientific publication submission(s) in AI conferences (e.g., NeurIPS, CVPR, ICCV, ICLR). Preferred qualifications: Master’s degree in a STEM field (e.g., Computer Science, Mathematics, or Statistics), or equivalent practical experience. Ability to work and collaborate across multiple teams and work with ambiguity. About the jobThe Post-doctoral Researcher role is a 12 to 24-month role designed to give you industry experience working on challenging problems together with Google DeepMind India scientists and engineers in India.As a Post-Doctoral Researcher, you will collaborate with researchers, scientists, and engineers at Google DeepMind India working on fundamental research and applied problems in a wide range of areas in Computing. You will have a wide range of opportunities ranging from conducting fundamental research and exploring their applications in products and services used by billions of people, and conducting research that contributes to human-centered AI and catalyzes AI for social good.Google DeepMind India addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field we publish regularly in top-tier conferences,academic journals, release projects as open source, and apply research to Google products.Responsibilities Work with research mentors to formulate research projects or novel applications of machine learning aligned with the team's mission. Conduct research and publish high quality work. Design and execute large-scale experiments, writing high-quality, reusable code, and contributing to a production-ready system using frameworks such as JAX. Learn and understand research in machine learning algorithms. Understand how to use research to drive design decisions. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

This role requires you to work in a shift pattern or non-standard work hours as required. This may include weekend work.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.

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 or equivalent practical experience. 2 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data. 2 years of experience managing projects and defining project scope, goals, and deliverables. Preferred qualifications: Master's degree in a quantitative discipline. 4 years of experience in the payments industry, working in risk or fraud management. 2 years of experience with one or more of the following languages: SQL, R, Python, or C++. 2 years of experience with machine learning systems. knowledge of one or more of the following areas: statistical analysis and machine learning libraries (e.g., R, Scikit-learn,Tensorflow), programming languages (e.g., Python, C/C++), Large Language Models (LLMs) or Generative AI. Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment. About the jobThe Trust and Safety team reduces risk and protects the experience of our users and business partners in more than 40 languages and across Google's expanding base of products. We defend Google's integrity by fighting spam, fraud and abuse, and develop and communicate product policies. We work with a variety of teams from Engineering to Legal, Public Policy and Sales Engineering to set policies and combat fraud and abuse in a scalable way, often finding industry-wide solutions. Trust and Safety team members are motivated to find innovative solutions, and use technical know-how, user insights and proactive communication to pursue the highest possible quality and safety standards for users across Google products.In this role, you will be responsible for restricting or preventing policy violators and abusers to ensure a safe and secure payment environment for our users. You will identify and solve complex problems and have strong investigative and technical skills to innovate and optimize our processes and tools. You will be proactive, motivated, organized, responsible, innovative and work well in a fast-paced, global, cross-functional, and team-oriented environment and demonstrate technical know-how, effective communication to get things done.Responsibilities Promote user trust and safety by managing and mitigating payment fraud and abuse for Google products and services. Investigate fraud and abuse incidents, identify patterns and trends in order to generate risk management solutions. Perform statistical analysis using payments and risk data warehouse, collaborate with Engineering and Product teams to create and enhance tools, develop signals, improve system functionality, accuracy and efficiency. Perform end-to-end assessment of the riskiness and vulnerability of products and features, design and implement fraud and abuse mitigation strategies. Engage and collaborate with cross-functional teams globally, work closely with engineers, product managers, and various internal and external stakeholders to launch risk mitigation solutions. 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.