Staff Software Engineer, Android Hotword

🏢 Summary: Software engineering role focused on developing and maintaining large-scale infrastructure or distributed systems. The position involves writing and reviewing code, improving technical documentation, and debugging product or system issues across hardware, network, and service operations. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 5 years of software development experience, 1 year of large-scale infrastructure or distributed systems experience, 1 year of data structures and algorithms experience 📃 Skills: Python, C, C++, Java, JavaScript, Algorithms, Golang, Rust 🏢 Description: Minimum qualifications • Bachelor’s degree or equivalent practical experience. • 5 years of experience with software development in one or more programming languages, such as Python, C, C++, Java, or JavaScript. • 1 year of experience building and developing large-scale infrastructure or distributed systems. • 1 year of experience with data structures and algorithms. Preferred qualifications • Master’s degree or PhD in Computer Science or a related technical field. • Experience developing accessible technologies. • Experience with backend coding languages such as Golang, Rust, or Java. • Experience with ML model coding languages, such as Python. About the job Responsibilities • Write product or system development code. • Review code developed by other developers and provide feedback to ensure best practices, including style guidelines, code check-in, accuracy, testability, and efficiency. • Contribute to existing documentation or educational content and adapt content based on product or program updates and user feedback. • Triage product or system issues and debug, track, and resolve them by analyzing issue sources and their impact on hardware, network, or service operations and quality.

🏢 Summary: Technical role focused on building AI-driven financial experiences by integrating third-party tools and agent workflows into an AIX orchestration layer. The position develops scalable, low-latency Generative UI capabilities and personalized financial insights using user signals, while leading architecture and delivery from discovery through production. 🗂️ Requirements: Bachelor’s degree in Computer Science, Software Engineering, or equivalent practical experience, 5 years of software development experience, Experience with C++, Java, Kotlin, Python, or another general-purpose programming language, Experience developing, prompt-tuning, fine-tuning, or orchestrating LLM and generative AI systems, Experience with algorithms, Experience architecting backend or infrastructure systems 📃 Skills: C++, Java, Kotlin, Python, LLMs, AI, Algorithms, Backend, Infrastructure, MCP, MaRS, Agency, GenUI 🏢 Description: Minimum qualifications: • Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience. • 5 years of software development experience in one or more general-purpose programming languages (e.g., C++, Java, Kotlin, Python). • Experience developing with, prompt-tuning, fine-tuning, or orchestrating Large Language Models (LLMs) and generative AI systems. • Experience with algorithms and architecting backend or infrastructure systems. Preferred qualifications: • Experience with tool execution pipelines, agentic workflows, function calling, or Model Context Protocol (MCP) integration. • Experience working with Generative UI pipelines, adaptive design architectures, or dynamic component rendering systems. • Familiarity with Google Search Next infrastructure, specifically MaRS, Agency, and GenUI ecosystem components. • High interest in personal finance, market intelligence, fintech, or complex transactional domains where high precision and factuality are paramount. Responsibilities: • Lead technical execution for connecting external third-party tools and partner agents into an AIX orchestration layer utilizing the Model Context Protocol (MCP). • Build scalable, low-latency Generative UI capabilities on top of Core Search Next platforms, including MaRS, Agency, and the GenUI framework, to transform raw financial output into actionable, interactive user experiences. • Integrate Zero-Party (0P), First-Party (1P), and Third-Party (3P) user signals to deliver tailor-made financial insights while setting new standards for strict factuality, multi-turn conversation context, and high-utility helpfulness. • Identify engineering gaps, set technical roadmap priorities, and guide initiatives from initial discovery through production deployment. • Build strong relationships with cross-functional partners in Product Management, User Experience, Research, Quality, and External Partner Integration to align technical goals with product strategy.

🏢 Summary: Lead the technical direction and end-to-end delivery of AutoCloud Agentic Systems. The role focuses on Generative AI, scalable software development, engineering best practices, and cross-functional alignment to deliver customer value. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 8 years of software development experience, 5 years of leadership, people management, hiring, mentoring, and talent-retention experience across global locations, 2 years of Generative AI experience 📃 Skills: GenerativeAI, Softwaredevelopment, AI, Prototyping, Deployment, Monitoring 🏢 Description: Minimum qualifications • Bachelor’s degree or equivalent practical experience. • 8 years of experience with software development. • 5 years of experience in leadership, people management, hiring, mentoring, and retaining talent across global locations. • 2 years of experience with Generative AI. Preferred qualifications • Master’s degree or PhD in Engineering, Computer Science, or a related technical field. • 5 years of experience working in a complex, matrixed organization. About the job Responsibilities • Lead the technical goal and execution for AutoCloud Agentic Systems, ensuring alignment with product goals and user needs. • Drive the end-to-end development life cycle of features, from ideation and prototyping to deployment, monitoring, and iteration, ensuring high quality, scalability, and performance. • Develop technology strategy and phased plans alongside product to drive product improvements or process simplifications. • Partner with cross-functional leaders across Google Cloud and AutoCloud to drive alignment and deliver customer value. • Define and advocate for best practices in AI development and software engineering, ensuring robust and reliable systems.

🏢 Summary: Technical leadership role managing a team that builds capacity-planning systems for high-throughput cloud storage products and large AI/ML workloads. The position owns strategy and delivery for distributed infrastructure solutions, network optimization, automated capacity adjudication, and cross-functional supply alignment. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 8 years of software development experience, 3 years of experience with large-scale infrastructure, distributed systems, networks, compute technologies, storage, or hardware architecture, 3 years of technical leadership experience, 2 years of people management or team leadership experience 📃 Skills: Software, Infrastructure, DistributedSystems, Networks, Compute, Storage, Hardware, CapacityPlanning, AI, ML 🏢 Description: Minimum qualifications • Bachelor’s degree, or equivalent practical experience. • 8 years of experience in software development. • 3 years of experience developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture. • 3 years of experience in a technical leadership role. • 2 years of experience in a people management or team leadership role. Preferred qualifications • Master's degree or PhD in Computer Science or a related technical field. • 3 years of experience working in a complex, matrixed organization. • Strong understanding of AI/ML frameworks. • Experience mentoring executive engineers and other technical leads. • Experience in capacity planning for complex, large-scale distributed systems. About the job Responsibilities • Manage team staffing and career growth, uphold a high-performance bar, and foster an environment to build capacity-planning solutions for high-throughput GCS products. • Own the strategy, scoping, navigation, and outcomes for capacity-planning systems targeting high-throughput scenarios, such as the Bandwidth Highway and Rapid Cache. • Guide the team through ambiguity by breaking down complex challenges, including supply scarcity and dense AI zone typologies, into tractable technical milestones. • Navigate complex relationships across GCS, Networking, Compute, and Data Center teams to align supply agendas and ensure seamless onboarding for massive AI/ML workloads. • Drive engineering efforts to automate capacity adjudication, optimize network resources, and accelerate the time required to onboard new high-throughput customers.

🏢 Summary: Research-focused Software Engineer role advancing large language model and information retrieval capabilities for Gemini, Search, and related products. The position combines model evaluation, multi-stage training and practical modeling innovations, with deployment of research advances alongside Search and YouTube teams. 🗂️ Requirements: Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, a related technical field, or equivalent practical experience, 3 years of machine learning experience focused on Large Language Models or Information Retrieval, 3 years of software engineering experience using Python, C++, JAX, or PyTorch, Experience implementing multi-stage training pipelines or algorithms 📃 Skills: Python, C++, JAX, PyTorch, LLMs, IR, MachineLearning 🏢 Description: Minimum qualifications • Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related technical field, or equivalent practical experience. • 3 years of experience in machine learning, with a focus on Large Language Models (LLMs) or Information Retrieval (IR). • 3 years of experience with software engineering in Python, C++, JAX, or PyTorch programming, including experience implementing multi-stage training pipelines or algorithms. Preferred qualifications • Experience developing Reinforcement Learning (RL) algorithms, automated evaluation systems, or LLM reflection and reasoning frameworks. • Experience with competitive programming, mathematics competitions (e.g., ICPC, IOI, IMO), or a track record of developing novel algorithms. • Experience rapidly prototyping and iterating on complex systems, generative AI models, or multi-stage pipelines. • Experience collaborating with product engineering teams to deploy machine learning models or research innovations into large-scale production environments (e.g., Search, Recommendation Systems). • Track record of learning new software tools, frameworks, and codebases quickly to solve complex technical obstacles. About the job Research-focused Software Engineers create experiments, prototype implementations, and design new architectures for real-world challenges such as artificial intelligence, data mining, natural language processing, hardware and software performance analysis, compilers for mobile platforms, and core search. The role includes large-scale testing and rapid deployment of promising ideas, while contributing to the wider research community through university partnerships and published papers. Responsibilities • Uncover strategic opportunities at the intersection of Gemini, Search, factuality, continual learning, deep research, and domain internalization. • Analyze models and model-driven products beyond current leaderboards; understand complex problem spaces and create new ways to measure ideal behavior. • Use empirical findings to develop practical interventions and modeling innovations that improve models across downstream surfaces. • Collaborate with product teams such as Search and YouTube to scale research innovations into production environments, optimizing for quality and efficiency.

🏢 Summary: Software engineering role focused on building and operating switch software for Google’s data-center network operating system. The position supports AI networking and high-performance TPU/GPU fabrics, with responsibility for scalable network performance, software delivery, and system issue resolution. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 5 years of software development experience, 3 years of software product testing, maintenance, or launch experience, 1 year of software design and architecture experience, 3 years of large-scale infrastructure, distributed systems, networks, compute, storage, or hardware architecture experience, Networking experience with L2, L3, ACL protocol layers, and SDN 📃 Skills: Networking, SDN, Linux, L2, L3, ACL, Multithreading, Infrastructure, DistributedSystems, Switching, TPU, GPU 🏢 Description: Minimum qualifications • Bachelor’s degree or equivalent practical experience. • 5 years of experience with software development in one or more programming languages. • 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture. • 3 years of experience developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture. • Experience with networking (L2/L3/ACL protocol layers) and SDN. Preferred qualifications • Master's degree or PhD in Computer Science, or a related technical field. • 5 years of experience with data structures and algorithms. • Experience developing accessible technologies. • Knowledge of Linux user space development and multi-threading development. About the job Software engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information. Products operate at massive scale and span areas including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design, and mobile. As a software engineer, you will work on a project critical to business needs, with opportunities to switch teams and projects as the business evolves. The role requires versatility, leadership, and enthusiasm for solving new full-stack problems. Join a high-performing team responsible for the network operating system powering data-center infrastructure. Contribute to projects enabling AI networking and high-performance fabrics for TPU and GPU workloads. The Platforms Infrastructure Engineering team designs and builds the hardware and software technologies that power services. Its computational challenges are complex and enabled by custom hardware designed and manufactured in-house. The work spans systems from concept through high-volume manufacturing and can shape the machinery used in cutting-edge data centers. Responsibilities • Design, develop, test, deploy, maintain, and improve switch software. • Manage individual project priorities, deadlines, and deliverables. • Manage scalability and performance tuning of large-scale networks. • Triage product or system issues and debug, track, and resolve them by analyzing their sources and impact on hardware, network, or service operations and quality.

🏢 Summary: Lead the architecture and scaling of AI/ML infrastructure for YouTube Ads creative automation. The role focuses on high-throughput distributed systems, GenAI media-processing pipelines, experimentation platforms, and technical leadership across product and research teams. 🗂️ Requirements: Bachelor’s degree in Computer Science, related technical field, or equivalent practical experience, 8 years of software development experience, 5 years of software product testing and launch experience, 5 years building large-scale infrastructure, distributed systems, networks, compute, storage, or hardware architecture, 3 years of software design and architecture experience, Experience designing or deploying machine-learning infrastructure or platforms 📃 Skills: Python, TensorFlow, PyTorch, Cloud, Distributed, Infrastructure, Architecture, Algorithms, MachineLearning, DeepLearning, GenAI 🏢 Description: Minimum qualifications • Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience. • 8 years of experience in software development. • 5 years of experience testing and launching software products. • 5 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture. • 3 years of experience with software design and architecture. • Experience designing or deploying machine learning (ML) infrastructure or platforms. Preferred qualifications • Master’s degree or PhD in Engineering, Computer Science, or a related technical field. • 8 years of experience with data structures and algorithms. • 3 years of experience in a technical leadership role leading project teams and setting technical direction. • 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects. • Proficiency in deep learning frameworks (e.g., TensorFlow, PyTorch) and cloud/distributed data technologies. About the job Develop next-generation technologies that operate at massive scale. Work on a project critical to business needs, with opportunities to switch teams and projects as priorities evolve. Bring ideas across areas including distributed computing, large-scale system design, networking, data storage, artificial intelligence, and more. Manage project priorities, deadlines, and deliverables. Design, develop, test, deploy, maintain, and enhance software solutions. The YouTube Ads Creative Optimization (YACO) team develops Creative Automation applications that drive advertiser value with minimal advertiser effort by leveraging AI technologies. The team operates at the intersection of Ads, YouTube, and Research. Responsibilities • Serve as the technical leader responsible for architecting, scaling, and steering next-generation infrastructure that powers AI/ML applications. • Operate at the intersection of Ads, YouTube, and GenAI research to build high-throughput systems enabling seamless creative generation and optimization. • Define the technical roadmap and architect scalable foundational infrastructure, including creative data engines, generation and rendering pipelines, and agentic orchestration frameworks. • Design and optimize distributed systems for complex GenAI and heavy media-processing workloads. • Build and mature experiment and learning infrastructure to accelerate model training, evaluation, and rapid deployment. • Partner with Product Management, Research, and executive leadership to align infrastructure capabilities with long-term business goals. • Guide, mentor, and elevate executive and junior engineers, fostering technical excellence and execution.

🏢 Summary: Lead Google Cloud AI Research engineering teams developing and deploying large-scale generative AI solutions. The role combines technical strategy, ML infrastructure optimization, system design, code development, and people leadership across multiple teams and locations. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 8+ years of software development experience, 5+ years leading ML design and ML infrastructure optimization, 3+ years in technical leadership, 2+ years with state-of-the-art GenAI techniques or related concepts, 2+ years of people management or team leadership experience 📃 Skills: Python, C, C++, Java, JavaScript, ML, GenAI, LLMs, Multimodal, Vision, Deployment, Evaluation, Debugging, Finetuning 🏢 Description: Minimum qualifications • Bachelor’s degree or equivalent practical experience. • 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript). • 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). • 3 years of experience in a technical leadership role. • 2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision). • 2 years of experience in a people management or team leadership role. Preferred qualifications • Master’s degree or PhD in Engineering, Computer Science, or a related technical field. • 3 years of experience working in an organization involving cross-functional or cross-business projects. About the job Software Engineering Managers provide technical leadership for major projects while managing teams of engineers. They manage project goals, contribute to product strategy, develop their teams, and help engineers optimize their code. This role manages engineers across multiple teams and locations, a large product budget, and the deployment of large-scale projects across multiple international sites. The Google Cloud AI Research team addresses AI challenges across industries including technology, healthcare, finance, and retail, conducting research with scientific and real-world impact and collaborating with product teams to bring innovations to customers. Responsibilities • Set and communicate team priorities that support broader organizational goals; align strategy, processes, and decision-making across teams. • Set clear expectations based on individuals’ levels and roles; meet regularly to discuss performance and development, and provide feedback and coaching. • Develop the mid-term technical vision and roadmap for one or more teams; evolve the roadmap for future requirements and infrastructure needs. • Design, guide, and vet system designs; write product or system development code to solve ambiguous problems. • Lead the design of GenAI solutions, optimize ML infrastructure, and guide data preparation and model optimization strategies.

🏢 Summary: This offer focuses on developing subscriber and engagement forecasting models, defining product metrics, and delivering analytics that improve subscription growth and engagement. The role partners with Data Science, leads quantitative analysis, and automates product-health reporting with AI-enabled tools. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 4 years of experience in an analytically intensive role 📃 Skills: SQL, Spreadsheets, Visualization, Forecasting, Analytics, Modeling, Automation, AI 🏢 Description: Minimum qualifications • Bachelor's degree or equivalent practical experience. • 4 years of experience with an analytically-intensive role, such as management consulting, investment banking, business intelligence, data science, or corporate strategy and operations. Preferred qualifications • 6 years of experience in an analytically-intensive role, such as management consulting, investment banking, business intelligence, data science, or corporate strategy and operations. • Experience in consumer internet, media, sports, or online video industries, especially with subscription products. • Experience driving cross-functional programs or projects, with exceptional communication skills and the ability to influence a range of audiences. • Strong problem-solving and quantitative skills, including experience with SQL, spreadsheets, data visualization, sophisticated forecast models, and other data analytics tools. About the job Responsibilities • Own the development of driver-based subscriber and engagement models. Translate complex business inputs into forecasts that define annual and quarterly goals (OKRs) and the 5-year business outlook. • Define core product-area metrics and become an expert in how and why those metrics move. Conduct detailed analyses that result in actionable insights to improve performance. • Partner with the Data Science team to prioritize and execute sophisticated quantitative analyses and advanced modeling that delivers actionable insights to grow subscriptions and engagement. • Automate core workflows for product-health reporting, leveraging AI tools to reduce manual overhead and provide more self-serve options for executives.

🏢 Summary: Opportunity to build and deploy ML and LLM-powered automation for keywordless Google Search Ads products. The role focuses on improving ad relevance, query understanding, and large-scale optimization while solving complex engineering problems that affect advertisers and users globally. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 2 years of Python or C++ programming experience, 1 year of experience in generative AI, reinforcement learning, large language modeling, model processing, or another ML specialization, 1 year of end-to-end machine learning experience, including deployment, evaluation, data processing, or debugging 📃 Skills: Python, C++, AI, ML, LLM, Deployment, Evaluation, Debugging, Algorithms 🏢 Description: Minimum Qualifications • Bachelor’s degree or equivalent practical experience. • 2 years of experience programming in Python or C++. • 1 year of experience with one or more of the following: generative AI, reinforcement learning (e.g., sequential decision making), large language modeling, model processing, or specialization in another ML field. • 1 year of experience with end-to-end machine learning (e.g., model deployment, model evaluation, data processing, debugging). Preferred Qualifications • Master’s degree or PhD in Computer Science or related technical fields. • 2 years of experience with data structures and algorithms. • Experience developing accessible technologies. Description The team builds AI-powered automation for Search Ads. Keywordless Search Ads supports products including Dynamic Search Ads, AI Max, Performance Max (PMax), and Smart Campaigns, helping advertisers connect with users effectively and efficiently. Keywordless Ads is a search-ads automation system that delivers highly relevant ads to users with minimal effort from advertisers. The role involves solving open-ended problems in a changing environment and directly impacting advertisers and users worldwide. Responsibilities • Write product or system development code. • Develop and deploy new ML/LLM models to directly impact Google, advertisers, and users. • Manage complex, open-ended engineering problems related to ad relevance, query understanding, and large-scale system optimization. • Triage product or system issues and debug, track, and resolve them by analyzing issue sources and their impact on hardware, network, or service operations and quality. • Implement solutions in one or more specialized ML areas, use ML infrastructure, and contribute to model optimization and data processing.