Senior Director, Chipset Systems and SoC Architecture

🏢 Summary: Staff CAD Engineer role focused on architecting, developing, and deploying the CI2 silicon design environment for next-generation TPU and AI/ML hardware. The position improves silicon development flows, iteration speed, and power, performance, cost, and quality outcomes through advanced tooling and cross-functional collaboration. 🗂️ Requirements: Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, related field, or equivalent practical experience, 10 years of technical leadership experience in critical silicon-design areas, Experience in at least two silicon disciplines, Experience developing and deploying advanced tools and development flows for the silicon lifecycle, Ability to lead design-environment architecture, development, and deployment, Knowledge of silicon development phases and scalable design flows 📃 Skills: Silicon, TPU, CI2, AI/ML, DFT, Synthesis, Verification, Firmware, Architecture, Modeling, Place-and-route, Timing, APIs 🏢 Description: Minimum qualifications • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience. • 10 years of experience in technical leadership focusing on one or more critical aspects of silicon design. • Experience in two or more silicon disciplines, including architecture modeling, logic design, functional verification, DFT, synthesis, place and route, timing analysis, physical verification, or firmware development. • Experience developing and deploying advanced tools and development flows that streamline the silicon lifecycle and improve engineering productivity. Preferred qualifications • Master's degree or PhD in Electrical Engineering, Computer Engineering, or Computer Science, with an emphasis on computer architecture. • 15 years of relevant academic and industrial experience in advanced silicon development. • Experience identifying the need for a silicon methodology change, developing a solution, and successfully deploying it with impact to more than 25 developers. • Experience developing solutions that require bridging knowledge gaps among collaborators. • Experience collaborating in internal or external ecosystem standardization efforts. • Knowledge of both front-end silicon development processes—architecture, logic design, and verification—and back-end processes—logic synthesis, place and route, timing convergence, and physical verification. About the job Shape the future of AI/ML hardware acceleration by driving TPU technology for demanding AI/ML applications. Develop custom silicon solutions and use design and verification expertise to verify complex digital designs, with a focus on TPU architecture and its integration within AI/ML-driven systems. As a Staff CAD Engineer, Silicon Design Environment, collaborate with domain experts across the silicon development spectrum to deliver the development environment for chips powering next-generation cloud systems. Refine ambiguous intent into solutions and rally others to develop or deploy them. Responsibilities • Use knowledge of silicon development phases to define the architecture and lead the development and deployment of the overall CI2 design environment as a coherent system of first-party and third-party tools, industry-standard and internal APIs/data formats, and scalable design flows. • Collaborate with technical leaders across CI2 sites to identify evolutionary and revolutionary tooling and methodology changes that enable convergence on a shared design environment. • Engage with other internal teams to keep CI2 at the forefront of advanced silicon development. • Ensure developed technologies optimize project iteration speed while achieving planned power, performance, cost, and quality metrics. • Partner with tools and methodologies team members to apply procedural and AI-first approaches that improve efficiency.

🏢 Summary: Senior Chip Package SI/PI Engineer role supporting TPU-based AI/ML hardware acceleration. The position drives chip-package-system co-design, simulations, characterization, methodology development, and electrical design closure for advanced 2.5D/3D packages. 🗂️ Requirements: Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, related field, or equivalent practical experience, 10 years of chip/package or system PCB SI/PI design experience, Experience with industry SI/PI modeling toolchains, SI/PI simulation and characterization experience at package and system level, Cross-functional collaboration with chip, board, system, and vendor teams 📃 Skills: HFSS, ADS, Sigrity, Siwave, SIPI, PCB, TPU, ASIC, Python, Matlab, C++, STA, EMIR, DFM 🏢 Description: Minimum qualifications: • Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience. • 10 years of experience with SI/PI design for chip/package or system PCB. • Experience with industry Signal Integrity and Power Integrity (SI/PI) modeling toolchains, such as HFSS, ADS, Sigrity, and Siwave. Preferred qualifications: • Master’s degree or PhD in Electrical Engineering or SI/PI. • Experience in 2.5D/3D package design, including silicon interposer, silicon bridge, and 3D die stacking technologies, with SI/PI analysis expertise for high-speed interconnects. • Knowledge of next-generation memory and chiplet standards, including timing budgets and design and sign-off methodologies. • Understanding of Static Timing Analysis, on-chip DVD/EMIR, system voltage budgets, and voltage regulator modeling and design. • Ability to lead cross-functionally across chip design, physical design, STA, packaging, system, and validation teams. • Proficiency in Python, Matlab, or C++ for automation flows and advanced data processing and analysis. In this role, you will help shape AI/ML hardware acceleration and drive TPU technology for demanding AI/ML applications. You will develop custom silicon solutions and contribute design and verification expertise for complex digital designs, with a focus on TPU architecture and its integration in AI/ML-driven systems. As a Chip Package Signal Integrity/Power Integrity (SI/PI) Engineer on the chip implementation team, you will be responsible for chip-package design, SI/PI simulation, and characterization at package and system level. You will work with system architects, ASIC engineers, SI/PI engineers, chip and board design teams, system design teams, and vendors to deliver chip packaging signal and power implementations that meet chip, package, and system electrical requirements. • Drive chip-package-system co-design through SI/PI analysis and optimization, contributing to product definition and optimizing chip floorplans, power-tree structures, and netlists for HPC using 2.5D/3D package technology. • Develop power-integrity methodologies for advanced package technology and improve methodology accuracy and productivity. • Evaluate new package technologies and high-speed interface IP. • Collaborate with chip design, system design, and supplier teams to establish chip-package SI/PI targets, define chip-design boundaries, and explore SI/PI and DFM trade-offs for package design closure in production. • Provide feedback on chip floorplans based on package and system routability and SI/PI considerations.

🏢 Summary: Lead a newly consolidated engineering team building the technical foundation for safe, scalable Google Cloud use across Alphabet, including AI solutions and infrastructure automation. The role combines people leadership, technical strategy, system design, and hands-on engineering for large-scale, international deployments. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 8 years of software development experience, 2 years of people management or team leadership experience, Experience integrating generative AI tools or LLM interfaces into workflows 📃 Skills: SoftwareDevelopment, GenerativeAI, LLMs, Leadership 🏢 Description: Minimum qualifications • Bachelor’s degree, or equivalent practical experience. • 8 years of experience in software development. • 2 years of experience in a people management or team leadership role. • Experience integrating generative AI tools or LLM interfaces into workflows. 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. • Experience or strong interest in building execution runtimes and sandboxes for AI/ML workloads or autonomous agent frameworks (e.g., Jetski, CASG, Vertex Agent Engine). • Experience managing corporate customer migration, intake pipelines, or onboarding workflows at scale. • Familiarity with Google Cloud security products (such as VPC Service Controls and Cloud Firewalls), as well as advanced networking technologies like eBPF network policies, Cilium, and Envoy sidecar proxies. • Familiarity with Google-internal production primitives and data access layers (F1, Spanner). About the job Software Engineering Managers provide technical leadership for major projects while managing teams of engineers. They optimize their own code, enable engineers to optimize theirs, manage project goals, contribute to product strategy, and develop their teams. Teams work across areas including information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, and user interface design. With technical and leadership expertise, you will manage engineers across multiple teams and locations, oversee a large product budget, and lead deployment of large-scale projects across multiple international sites. The Hybrid Cloud Environment (HCE) team enables Alphabet’s safe-by-default use of Google Cloud Platform (GCP) by shifting non-functional requirements—including security, privacy, regulatory, and FinOps—into the platform layer. You will lead a newly consolidated engineering team combining the former Cloud AI Solutions and Corp Run workstreams; the team will support Cloud for Alphabet (C4A) and Project Reef, making “intent become infrastructure.” The Core team builds the technical foundation behind flagship products. The team owns and advocates for underlying design elements, developer platforms, product components, and infrastructure; builds central solutions across products; removes technical barriers; strengthens existing systems; and influences important technical decisions across the organization. Responsibilities • Set and communicate team priorities that support broader organizational goals. • Align strategy, processes, and decision-making across teams. • Set clear expectations for individuals based on their level and role, aligned with organizational goals. • Meet regularly with individuals to discuss performance and development, and provide feedback and coaching. • Develop the mid-term technical outlook and roadmap for one or more teams. • Evolve the roadmap to meet anticipated future requirements and infrastructure needs. • Design, guide, and vet system designs within the broader area, and write product or system development code to solve ambiguous problems. • Review engineers’ code and provide feedback to ensure best practices for style, code check-in, accuracy, testability, and efficiency.

🏢 Summary: Lead the end-to-end architecture of DRAM memory subsystems and controllers for consumer SoCs, driving performance, power, area, and hardware-software co-design. The role includes defining specifications, evaluating designs through modeling and simulation, and partnering with design, verification, emulation, and software teams on next-generation memory technologies. 🗂️ Requirements: Bachelor’s degree in Electrical Engineering, Computer Science, Computer Engineering, or equivalent practical experience, 15 years of industry experience in memory controller architecture, microarchitecture, or ASIC design, Experience designing DRAM memory controller architectures and microarchitectures, Experience with ASIC performance analysis, performance tools, and simulator development across abstraction levels 📃 Skills: DRAM, ASIC, SoC, TLM, C, DDR 🏢 Description: Minimum Qualifications • Bachelor’s degree in Electrical Engineering, Computer Science, Computer Engineering, or equivalent practical experience. • 15 years of industry experience in memory controller architecture, micro-architecture, or ASIC design. • Experience in architecture, micro-architecture, and design of DRAM memory controllers. • Experience in ASIC architecture performance analysis, performance tools, and simulator development at different abstraction levels, such as cycle-accurate, TLM, or functional. Preferred Qualifications • Master’s degree or PhD in Electrical Engineering, Computer Engineering, or Computer Science, with an emphasis on computer architecture. • Deep domain knowledge in coherent interconnects, caches, fabrics, memory systems, and memory controllers. • Understanding of hardware performance monitors, profiling, power management, and optimization. Description Shape the future of DRAM memory subsystem and controller architecture for consumer SoCs. Bring together the architectural responsibilities for memory subsystems and memory controllers to drive architectural alignment, performance optimization, and hardware-software co-design. Collaborate with hardware designers, validation teams, and software architects to build and test technologies. Work on memory system innovation using developments in DDR, process-in-memory, and other emerging DRAM advancements. Responsibilities • Define and maintain the end-to-end architectural strategy across memory subsystems and memory controllers for consumer SoCs. • Lead performance, power, and area trade-off analyses, feature design, clocking, and power-state management across memory IPs. • Author comprehensive hardware architectural specifications, system-level design requirements, and programmer guides for next-generation memory controllers. • Evaluate architectural choices by developing C models, executing workload simulations, and collaborating with verification and emulation teams. • Serve as the primary technical contact for memory path latency, power optimization, and performance across cross-functional engineering teams.

🏢 Summary: Lead manufacturing test engineering for hardware systems, managing a team and developing scalable test strategies, automation, and process improvements. The role addresses complex product failures through RCCA, data collection, and manufacturing-process qualification for server, storage, and networking hardware. 🗂️ Requirements: Bachelor’s degree in Computer Science, Electrical Engineering, or equivalent engineering experience, 10 years of test engineering experience in electronics manufacturing, 8 years of people management experience, Python, Bash, and Shell scripting experience for product-specific test plans and test execution 📃 Skills: Python, Bash, Shell, RCCA, ICT, BSCAN 🏢 Description: Minimum qualifications • Bachelor’s degree in Computer Science, Electrical Engineering, or equivalent engineering experience. • 10 years of experience in Test Engineering in electronics manufacturing. • 8 years of experience in people management. • Experience coding in Python, Bash, and Shell scripting to generate product-specific test plans and execute testing accordingly. Preferred qualifications • Experience in manufacturing, quality, or product engineering for hardware technology and systems. • Experience working with server, storage, and networking products, especially AI and ML servers, racks, and integration. • Experience with test station bring-up, gauge R&R/correlation, and partner or agreement manufacturing (ODM, OEM, JDM). • Experience managing manufacturing test hardware using custom electronics, fixturing, instrumentation, and defining test strategy, test automation, test optimization, and scaling test capacity. • Experience with design for test and structural tests such as ICT/BSCAN, Board- and System-level Functional Tests. • Ability to drive improvement of test systems and processes for scaling test capacity. About the job Join a team developing custom silicon solutions that support direct-to-consumer hardware products. Contribute to next-generation hardware experiences focused on performance, efficiency, and integration, while supporting the technical infrastructure behind data centers, platforms, and networks. Responsibilities • Lead a team; set and communicate individual and team priorities that support organizational goals. • Meet regularly with individuals to discuss performance and development, and provide feedback and coaching. • Apply Root Cause Corrective Action (RCCA) fundamentals and collaborate with teams to analyze failures and resolve issues. • Define and execute data-collection activities for highly complex technical issues. • Drive process design, optimization, and qualification activities for manufacturing processes involving components, parts, or products.

🏢 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: Senior embedded software engineering role focused on designing, developing, testing, deploying, and maintaining large-scale infrastructure software. The position provides technical leadership for high-impact projects, aligns distributed teams, and manages delivery priorities and timelines. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 8 years of software development experience, 7 years of embedded operating systems experience, 5 years of software design, architecture, testing, and product-launch experience, Kernel programming experience, Firmware experience, C or C++ coding experience 📃 Skills: C, C++, Kernel, Firmware, Embedded, Networking, Algorithms, Architecture 🏢 Description: Minimum qualifications • Bachelor's degree or equivalent practical experience. • 8 years of experience in software development. • 7 years of experience working with embedded operating systems. • 5 years of experience with design and architecture; and testing/launching software products. • Experience in Kernel programming and firmware. • Coding experience in C or C++. 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. • 5 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. • Experience with data center networking. About the job Software engineers develop next-generation technologies that support large-scale information services and products. This role works on a project critical to business needs, with opportunities to change teams and projects as priorities evolve. Engineers are expected to be versatile, demonstrate leadership, and take on new full-stack problems. Using technical expertise, you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. The AI and Infrastructure team delivers AI and infrastructure capabilities at scale, with a focus on efficiency, reliability, and velocity. Its work spans software and hardware, including TPUs, Vertex AI for Google Cloud, global networking, data-center operations, systems research, and hyperscale computing platforms. Responsibilities • Provide technical leadership on high-impact projects. • Influence and coach a distributed team of engineers. • Facilitate alignment and clarity across teams on goals, outcomes, and timelines. • Manage project priorities, deadlines, and deliverables. • Design, develop, test, deploy, maintain, and enhance large-scale software solutions.

🏢 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: 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 development of core on-device infrastructure for agentic and AI-driven Pixel experiences. The role focuses on Android system services, APIs, IPC, and optimized AI pipelines that deliver privacy-preserving, low-latency features directly to Pixel users. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 5 years of software programming experience, 3 years of experience testing, maintaining, or launching software products, 1 year of software design and architecture experience, 3 years of large-scale systems development or end-to-end Android infrastructure experience 📃 Skills: C++, Java, Python, Go, Android, IPC, APIs, Architecture, Algorithms, AI, MachineLearning 🏢 Description: Minimum qualifications • Bachelor’s degree or equivalent practical experience. • 5 years of experience with software programming in C++, Java, Python, or Go. • 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 systems or building Android infrastructure end-to-end. Preferred qualifications • Master’s degree or PhD in Computer Science or a related technical field. • 5 years of experience with data structures and algorithms. • 1 year of experience in a technical leadership role. • 1 year of experience in Android development. • Experience developing machine learning, artificial intelligence, or agentic experiences. • Experience with on-device machine learning execution. 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, data storage, security, artificial intelligence, natural language processing, UI design, and mobile. This role is on the Pixel team, which builds system-integrated experiences for Pixel smartphones. The team bridges advanced on-device AI models and the native Android OS to create integrated, intelligent features such as Magic Cue and Pixel Screenshots. You will lead the architecture, design, and implementation of core on-device infrastructure for agentic and AI-driven user experiences. You will build robust system-level frameworks and IPC/APIs that provide rich device context to on-device AI pipelines, enable multimodal intent execution, and interface with native Android platform subsystems. You will collaborate with teams across Pixel Software, Android Platform, and AI/ML to deliver end-to-end features for Pixel users. Responsibilities • Architect and build high-performance on-device infrastructure for intelligent workflows and AI experiences. • Design system services and APIs to collect and process rich, privacy-preserving device context for proactive AI interactions. • Partner with Pixel product teams, Android OS platform engineers, and AI research teams to deliver OS-level integrations and establish scalable system boundaries. • Optimize on-device pipelines for low latency, minimal memory footprint, and high power efficiency.