Senior Performance Co-Design Engineer, TPU

🏢 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: Customer Engineer role partnering with sales teams to design and demonstrate Google Cloud solutions for customers. The position leads technical discovery, demos, pilots, solution architecture, and delivery planning to win and expand cloud workloads. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 6 years of cloud computing experience, 6 years of presentation delivery experience, Experience presenting to technical stakeholders and executive leaders 📃 Skills: Cloud, GoogleCloud, A2A, LangGraph, CrewAI, AutoGen, VertexAI, LLM, TTFT, MCP, Authentication, Quantization 🏢 Description: Minimum qualifications • Bachelor's degree or equivalent practical experience. • 6 years of experience with cloud computing and delivering presentations. • Experience engaging with, and presenting to, technical stakeholders and executive leaders. Preferred qualifications • Experience navigating AI infrastructure consumption models and optimizing high-throughput training/inference clusters. • Experience implementing multi-agent systems using frameworks such as A2A, LangGraph, CrewAI, and AutoGen. • Experience navigating the startup life cycle, from initial prototyping with AI Studio to scaling and achieving product-market fit on Vertex AI. • Experience working with, and a passion for, the high-growth startup ecosystem and its typical rapid-scaling issues. • Knowledge of LLM-native performance metrics, including TTFT, tokens/sec, and cost-per-request, and techniques for optimizing state management, quantization, and provisioned throughput. • Ability to implement secure agentic workflows incorporating MCP, tool-calling, and enterprise-grade authentication. About the job As a Customer Engineer, you will partner with technical sales teams to differentiate cloud solutions for customers. You will serve as the customer’s primary technical partner and trusted advisor, leading technical conversations to understand business issues. You will troubleshoot technical questions and roadblocks, participate in proofs of concept and demos, and architect cross-pillar cloud solutions. You will drive the technical win, define delivery and consumption plans, and present practical solutions to technical and business leaders. You will identify, pursue, and win new business workloads while expanding existing ones. The role requires broad technical expertise across infrastructure modernization, application modernization, data analytics, and related areas, combined with sales expertise, market knowledge, and direct technical engagement. Responsibilities • Develop and own the technical account plan and strategy, participating in planning and supporting targeted sales motions. • Combine sales, programming, and solutions architecture expertise to prove the value of the cloud portfolio through complex demos, pilots, and in-depth workshops. • Architect cross-pillar solutions, drive technical wins, and define initial delivery plans for customers; continue to lead technical engagement during the solution phase. • Facilitate the post-sales transition by supporting pricing activities and transitioning the final delivery plan to implementation teams. • Maintain awareness of progress against the delivery plan, providing support to cross-functional teams during ramp, delivery, migration, or implementation phases.

🏢 Summary: This offer is for a senior software engineer to build conversational AI-agent capabilities, including recommendation systems, skill discovery and performance investigation tools. The role combines ML system design and infrastructure with technical leadership, stakeholder management and team coaching. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 5 years of software development experience, 5 years of software product testing and launch experience, 3 years of software design and architecture experience, 5 years of experience in speech/audio, reinforcement learning, ML infrastructure, or another ML specialization, 5 years of ML design and ML infrastructure experience, including deployment, evaluation, data processing, debugging or fine-tuning 📃 Skills: Python, MachineLearning, ReinforcementLearning, Speech, Audio, MLOps, Deployment, Evaluation, Debugging, Finetuning, Algorithms, Architecture 🏢 Description:

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🏢 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: Lead Technical Program Manager role driving the development and production delivery of next-generation AI/ML GPU systems and infrastructure solutions for cloud and technical infrastructure use cases. The individual contributor will lead cross-functional hardware and software programs, manage schedules and risks, and align technical execution across engineering, product, data center, networking, supply chain, and operations teams. 🗂️ Requirements: Bachelor’s degree in a technical field or equivalent practical experience, 5 years of program management experience, Experience launching new products across hardware, software, and systems infrastructure, Experience with data center infrastructure and deployment 📃 Skills: Programmanagement, Hardware, Software, Infrastructure, Datacenters, GPU, IaaS, VM, Baremetal, Distributedsystems 🏢 Description: Minimum Qualifications • Bachelor's degree in a technical field, or equivalent practical experience. • 5 years of experience in program management. • Experience in launching new products (NPI), encompassing hardware and software development, and systems infrastructure. • Experience with data center infrastructure and deployment. Preferred Qualifications • 5 years of experience managing cross-functional or cross-team projects. • Experience in hardware engineering, software engineering, GPU systems, and solutions. • Experience launching IaaS VM, bare metal, and machine-of-the-day products. • Ability to assess engineering problems and understand large-scale distributed systems. About the Job As a Technical Program Manager, you will use technical expertise to lead complex, multidisciplinary projects from start to finish. You will work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate with cross-functional partners. You will explain analyses and recommendations to executives and discuss technical tradeoffs in product development with engineers. The Platforms Infrastructure Engineering Program Management Office partners with compute engineering, networking, data center, supply chain, and operations teams to deliver AI/ML and standard compute systems and solutions supporting cloud IaaS and technical infrastructure services. This individual contributor role serves as the lead Technical Program Manager driving system and solution development for next-generation AI/ML GPU systems for cloud and technical infrastructure use cases. Responsibilities • Lead a cross-functional team across organizational levels and functional areas to develop and deliver hardware programs from inception to production. • Set program vision and direction by defining goals and objectives, evaluating and supervising multiple projects, organizing cross-project work, and establishing program controls, governance, and standards. • Use technical judgment to drive project delivery, conduct technology reviews, challenge proposals, build consensus, and align cloud and central processes. • Develop project documentation, process maps, presentations, and tracking reports that provide detailed project status. • Engage with engineering directors, product leaders, and Technical Program Manager groups to streamline processes, simplify execution, manage OKRs, support on-time releases, introduce efficiency tooling, and help teams execute.

🏢 Summary: Software engineering role focused on building and operating large-scale technical infrastructure, distributed systems, networks, and cloud platforms. The position involves end-to-end development, design reviews, code quality, documentation, and troubleshooting of system, hardware, network, and service issues. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 2 years of programming experience in C++, Python, or Go, 2 years of experience with large-scale infrastructure, distributed systems, networks, cloud technologies, storage, or hardware architecture 📃 Skills: C++, Python, Go, Cloud, Storage, Networks, Infrastructure 🏢 Description: Minimum qualifications • Bachelor’s degree or equivalent practical experience. • 2 years of experience programming in C++, Python, or Go. • 2 years of experience developing large-scale infrastructure, distributed systems, or networks; or experience with cloud computing technologies, storage, or hardware architecture. Preferred qualifications • Master’s degree or PhD in Computer Science or a related technical field. • 2 years of experience with performance analysis, large-scale systems data analysis, visualization tools, or debugging. • 2 years of experience with data structures or algorithms in an academic or industry setting. • Experience developing accessible technologies. • Proficiency in code and system health, diagnosis and resolution, and software test engineering. About the job Software engineers develop next-generation technologies that support 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 development. This role is assigned to a project critical to technical infrastructure needs, with opportunities to move between teams and projects as business needs evolve. Engineers are expected to be versatile, demonstrate leadership, and take on new full-stack challenges. The Technical Infrastructure team develops and maintains data centers, platforms, and networks that support products and services. The AI and Infrastructure team delivers AI and infrastructure capabilities at scale, with work spanning hyperscale computing, TPUs, Vertex AI, global networking, data center operations, systems research, software, and hardware. Responsibilities • Write product or system development code. • Participate in or lead design reviews with peers and stakeholders to select among available technologies. • Review code from other developers and provide feedback on best practices, including style guidelines, code check-in, accuracy, testability, and efficiency. • Contribute to documentation or educational content, adapting it for product or program updates and user feedback. • Triage, debug, track, and resolve product or system issues by analyzing their sources and impacts on hardware, network, or service operations and quality.

🏢 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 maintaining large-scale technical infrastructure that powers global services. The position involves product and systems development, design and code reviews, documentation, and debugging issues across hardware, network, and service operations. 🗂️ Requirements: Bachelor’s degree or equivalent practical experience, 2 years of programming experience in C++, Python, or Go, 2 years of experience with large-scale infrastructure, distributed systems, networks, compute technologies, storage, or hardware architecture 📃 Skills: C++, Python, Go, Infrastructure, Networks, Compute, Storage 🏢 Description: Minimum qualifications • Bachelor’s degree or equivalent practical experience. • 2 years of experience programming in C++, Python, or Go. • 2 years of experience developing large-scale infrastructure, distributed systems, or networks; or experience with compute technologies, storage, or hardware architecture. Preferred qualifications • Master’s degree or PhD in Computer Science or related technical fields. • 2 years of experience with performance, large-scale systems data analysis, visualization tools, or debugging. • 2 years of experience with data structures or algorithms in an academic or industry setting. • Experience developing accessible technologies. • Proficiency in code and system health, diagnosis and resolution, and software test engineering. About the job Software engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Products handle information at massive scale and extend beyond web search. As a software engineer, you will work on a project critical to business needs, with opportunities to switch teams and projects as the business grows and evolves. Engineers are expected to be versatile, demonstrate leadership, and take on new full-stack problems. The Technical Infrastructure team builds the architecture behind online user experiences. Its work includes developing and maintaining data centers, building next-generation platforms, and keeping networks running to provide users with a fast, reliable experience. The AI and Infrastructure team delivers AI and infrastructure at scale, efficiency, reliability, and velocity for internal teams, cloud customers, and users worldwide. Teams support AI-model development, global computing services, and developer platforms, with work spanning software and hardware, including TPUs, Vertex AI for Google Cloud, global networking, data center operations, and systems research. Responsibilities • Write product or system development code. • Participate in or lead design reviews with peers and stakeholders to select among available technologies. • 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: 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.