Currently tracking 498 active AI roles, down 12% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $98k–$1030k (avg $233k).
Google has 584 active AI-related job listings. The majority of these roles are focused on agents, representing 40% of the total, and serving infrastructure, at 26%. The most frequent technical tags include model_serving, agent_orchestration, and evals. Over the last 30 days, Google has added 413 new AI roles, a 105% increase compared to the preceding 30-day period.
Google currently has 586 active AI-related roles in our index. The most common open titles are: Software Engineer (5), AI Adoption Customer Engineer, Google Cloud (3), Conversational AI Consultant (2), Engineering Manager, Egregious Abuse Protection (2), Forward Deployed Engineer III, Generative AI, Google Cloud (2). Most positions are in Engineering and Product.
Google's active AI hiring is concentrated in: agents (43%), serving infrastructure (25%), application (19%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Google is hiring AI talent in: United States (376 roles), India (53 roles), Singapore (40 roles), Switzerland (20 roles).
Job postings at Google most frequently mention: Software Engineering, Algorithms & Data Structures, System Design, Computer Architecture, Machine Learning.
In the past 30 days, Google has posted 571 new AI-related roles. That is a +22% change versus the prior 30 days (469 → 571).
| Title | Stage | AI score |
|---|---|---|
| Senior Software Engineer, DeepMind Senior Software Engineer at Google DeepMind focused on building and enhancing serving solutions for Gemini models, developing new infrastructure for advanced capabilities like streaming and audio logic, and ensuring model quality in production. The role involves driving technical vision and roadmap for the team. | ServeAgent | 9 |
| Engineering Manager, ML Performance Engineering Manager for Google's TPU Performance team, focusing on optimizing the speed and efficiency of AI/ML model training and inference on custom TPU hardware. The role involves leading a team to develop and maintain ML benchmarks, identify performance opportunities, drive optimizations (near-term and out-of-the-box), and participate in algorithmic innovations and co-designing TPU-friendly models. This includes work on inference serving, quantization, and compiler optimizations, serving both internal Google teams and external AI companies. |
| ServePost-train |
| 9 |
| Senior Research Engineer, On-Device Inference, Robotics, DeepMind Senior Research Engineer focused on optimizing Gemini Robotics models for low-latency on-device inference, driving alignment between model and hardware architectures, and influencing future model designs for resource-constrained environments. | ServeAgent | 9 |
| Senior Software Engineer Senior Software Engineer at Google DeepMind focused on building and enhancing serving solutions for Gemini models, developing new infrastructure for advanced capabilities like multimodal understanding, and ensuring model quality in production. The role involves collaboration, driving technical vision, and working with large-scale production systems and machine learning specialization. | ServeAgent | 9 |
| Senior Software Engineer Senior Software Engineer role focused on building and enhancing serving solutions for Gemini models, developing new infrastructure for advanced capabilities like large-scale streaming and audio logic, and ensuring the quality of models in production. The role involves collaborating with peers, driving technical vision, and requires experience in C++, algorithm design, debugging ML systems, and productionizing LLMs/multimodal models. | ServeAgent | 9 |
| Staff Engineer, TPU Co-Design Staff Engineer focused on co-designing TPU hardware for AI/ML applications, bridging model architecture innovation with next-generation hardware design. Responsibilities include optimizing the hardware/software stack for ML model training and serving, developing simulators, and conducting system-level performance analysis. | ServePost-train | 9 |
| Senior Staff Engineer, TPU Co-Design Senior Staff Engineer focused on co-designing TPU hardware for AI/ML training and serving. The role involves defining the hardware/software roadmap, bridging AI research with hardware design, and optimizing performance for large ML models. This position operates at the intersection of AI research and infrastructure engineering, aiming to deliver high-performance, power-efficient accelerators. | ServePretrain | 9 |
| Machine Learning Hardware Architect, Hardware, Software Co-Design, Google Cloud This role focuses on architecting and defining the roadmap for AI/ML hardware acceleration, specifically TPUs, for Google Cloud. It involves co-design between model architecture and next-generation hardware, optimizing for ML serving and training capabilities, and integrating large-scale foundation models with advanced silicon architectures. The role requires defining technical roadmaps, architecting simulation frameworks, guiding system-level performance analysis, and managing cross-functional partnerships across hardware, compiler, and ML teams. | ServePost-train | 9 |
| Staff Software Engineer, AI/ML Performance Staff Software Engineer focused on optimizing AI/ML training and serving workloads on TPUs. The role involves identifying performance opportunities, driving optimizations through custom kernels, compiler/runtime improvements, and algorithmic innovation. It also includes co-designing TPU-friendly models and working with frontier lab hyperscalers and foundation model builders. | ServePost-train | 9 |
| Research Scientist, Efficient AI Research Scientist focused on developing resource-efficient AI architectures, training/inference recipes, and model compression techniques to make ML models faster and smaller, enabling efficient deployment on Google's infrastructure. The role involves independent research, translating ideas to experiments, and contributing to the research community through publications. | ServePost-train | 9 |
| Staff Software Engineer, AI/ML GenAI, Google Cloud Applications AI Staff Software Engineer role at Google Cloud AI Research focusing on designing, developing, and deploying large-scale GenAI solutions. The role involves technical leadership, optimizing ML infrastructure, guiding data preparation and model optimization, and working with LLMs, Multi-Modal, and Large Vision Models. Experience with ML design, infrastructure, and GenAI techniques is required. | ServePost-train | 9 |
| Staff Research Scientist, ML Efficiency, Google Research Research Scientist focused on improving the computational efficiency of large-scale generative AI models (LLMs, Diffusion Models, Generative Videos) through advanced algorithms, model compression, quantization, and optimization of training and inference pipelines. Collaborates with hardware and software teams to optimize kernels and inference engines. | ServePost-train | 9 |
| Research Scientist, ML Efficiency, Google Research Research Scientist focused on improving the computational efficiency of large-scale Generative AI Models (LLMs, Diffusion Models, Generative Videos) through algorithmic research, model compression, and inference acceleration. The role involves advancing algorithms for serving and inference, innovating training architectures, optimizing deployment pipelines, and collaborating with hardware/software teams. A PhD and publication record are required. | ServePost-train | 9 |
| Senior Research Scientist, ML Efficiency, Google Research Research Scientist focused on improving the computational efficiency of generative AI models (LLMs, Diffusion Models, Generative Videos) through foundational research in algorithmic efficiency, model compression, and inference acceleration. This role involves innovating algorithms, optimizing model architectures, improving the deployment pipeline (pretraining, tuning, RL), and collaborating with hardware/software teams to optimize inference engines and reduce latency/memory usage. | ServePost-train | 9 |
| Senior Research Engineer, On-Device Inference, Robotics, DeepMind Senior Research Engineer focused on optimizing Gemini Robotics models for low-latency on-device inference, driving alignment between model architectures and edge device constraints, and influencing research and engineering teams for robust solutions. Requires deep knowledge of inference techniques across GPU, TPU, and CPU architectures. | ServeAgent | 9 |
| Power and Performance Architect, TPU This role focuses on defining and driving the power architecture roadmap for Google's next-generation TPUs, which are AI/ML hardware accelerators. The architect will bridge the gap between high-level concepts and silicon execution, optimizing for performance-per-watt for ML workloads and ensuring successful implementation of power management features. This involves collaboration with various teams, including SOC implementation, hardware/software validation, and data center operations, to align silicon capabilities with system-level power constraints. The role requires deep expertise in computer chip design, performance analysis, and power analysis, with a strong emphasis on machine learning accelerator architecture and workload characterization for power optimization. | Serve | 9 |
| Senior Software Engineering Manager, Emergent AI Infrastructure Senior Software Engineering Manager for Emergent AI Infrastructure, leading teams to build next-generation on-prem AI infrastructure for frontier models and AI solutions. Role involves technical leadership, team management, strategic guidance, and cross-functional collaboration across global sites to deliver high-impact AI infrastructure products. | Serve | 9 |
| Staff Software Engineer, AI/ML GenAI, Google Cloud AI Staff Software Engineer at Google Cloud AI Research focused on designing, developing, and deploying GenAI solutions. This role involves leading the design of GenAI solutions, optimizing ML infrastructure, and guiding the development of data preparation and model optimization strategies. Requires significant experience in software development, ML infrastructure optimization, and state-of-the-art GenAI techniques. | ServePost-train | 9 |
| Staff Software Engineer, AI/ML Performance Staff Software Engineer focused on optimizing AI/ML training and serving workloads on TPUs. This role involves identifying performance bottlenecks, driving optimizations through custom kernels, compiler/runtime improvements, and collaborating with partner teams to achieve state-of-the-art performance for foundation model builders and hyperscalers. The position also involves algorithmic innovation and co-designing TPU-friendly models. | ServePost-train | 9 |
| Staff Software Engineer, GPU Performance Staff Software Engineer focused on optimizing GPU performance for LLM training and serving within Google Cloud's AI infrastructure. This role involves identifying performance bottlenecks, running benchmarks, and implementing solutions at scale, with a strong emphasis on low-level GPU programming and compiler optimizations. | Serve | 8 |
| Senior Software Engineer, AI Core Capabilities Senior Software Engineer focused on end-to-end delivery and optimization of on-device GenAI capabilities for Android, building developer-facing APIs and optimizing inference for Gemini Nano models. | ServeAgent | 8 |
| Senior Software Engineer, Sensor AI/ML, Watch Software Senior Software Engineer focused on AI/ML for sensor fusion and gesture recognition on Google's Pixel Watch and Fitbit devices. The role involves designing, training, and optimizing AI models for resource-constrained, on-body devices, with a strong emphasis on real-time inference, low-power formats (TFLite Micro), and C/C++ development for embedded systems. This position bridges research and engineering, requiring expertise in model optimization and deployment on edge devices. | ServePost-train | 8 |
| Customer Engineer, Public Sector Customer Engineer role focused on architecting and managing Large Language Model (LLM) deployments, including on-premises and cloud environments. The role involves auditing multi-agent orchestration, agent construction, and vector databases, orchestrating scalable inference and training environments using Docker and Kubernetes, and securing the MLOps lifecycle against AI-specific threats. Requires significant experience in AI/ML development, infrastructure engineering, and container orchestration. | ServeAgent | 8 |
| Staff Software Engineer, AI/ML GenAI, Google Cloud Staff Software Engineer at Google Cloud focused on designing, developing, and deploying large-scale GenAI solutions. The role involves leading ML infrastructure optimization, guiding data preparation and model optimization strategies, and working with state-of-the-art GenAI techniques like LLMs and Large Vision Models. Requires significant experience in software development, ML infrastructure, and GenAI. | ServePost-train | 8 |
| Software Engineer lll, AI Developer Tools Platform Software Engineer III on the AI Developer Tools Platform team, focusing on integrating Generative AI and LLMs for Cloud customers. Responsibilities include designing and implementing the platform, collaborating with researchers and product managers, and managing project priorities. Requires experience with ML infrastructure and software development. | ServeAgent | 8 |
| Software Engineering Manager II, AI/ML, Google Cloud Compute Software Engineering Manager II for Google Cloud Compute, responsible for leading teams, setting technical vision, and overseeing the design and implementation of ML solutions, including ML infrastructure optimization and model development strategies. Requires strong software development and ML experience, with a focus on leadership and people management. | ServeData | 8 |
| Software Engineer, AI/ML, Google Research Software Engineer role at Google Research focusing on implementing ML solutions, utilizing ML infrastructure, and contributing to model optimization and data processing. Requires experience in specialized ML areas like speech/audio, reinforcement learning, or ML infrastructure, with a focus on model deployment, evaluation, optimization, and data processing. | ServeData | 8 |
| Customer Engineer, Public Sector Customer Engineer for Google Cloud Public Sector, focusing on architecting and managing LLM deployments, including on-premises and cloud environments. Responsibilities include auditing multi-agent orchestration, agent construction, vector databases, orchestrating inference and training with Docker/Kubernetes, securing model weights and data, and mitigating AI-specific threats. Requires extensive experience in AI/ML development, infrastructure, and containerization, with a strong security clearance. | ServeAgent | 8 |
| Senior Silicon System and Software Integration Engineer, Google Cloud This role focuses on the hardware-software integration and validation of AI/ML accelerators (TPUs) for Google Cloud. The engineer will work on ASIC development, validation, software, tools, and methodologies to ensure the functionality and performance of these custom silicon solutions that power Google's AI/ML applications. | Serve | 8 |
| Senior Software Engineer, Applied AI/ML, CSP Senior Software Engineer role focused on Applied AI/ML within the Content Safety Platform at Google. The role involves technical leadership, designing and developing large-scale software solutions, and optimizing ML infrastructure. Key responsibilities include safeguarding users from harmful content, influencing technical direction, mentoring engineers, and leading the implementation of ML solutions, model optimization, and data processing strategies. Experience in speech/audio, reinforcement learning, or other ML fields, along with ML infrastructure experience, is required. | ServePost-train | 8 |
| Software Engineering Manager II, AI/ML, Google Cloud Software Engineering Manager II for Google Cloud, focusing on AI/ML. This role involves technical leadership, people management, setting team priorities, developing roadmaps, designing systems, and leading the implementation of ML solutions, including ML infrastructure optimization, model optimization, and data processing strategies. Requires significant experience in software development, ML infrastructure, and technical/people leadership. | ServeData | 8 |
| Silicon RTL Design Engineer, PhD, Google Cloud This role focuses on designing and verifying custom silicon solutions (TPUs) for AI/ML hardware acceleration within Google Cloud. The engineer will shape the future of TPU technology by architecting, modeling, and designing next-generation TPUs, optimizing for performance, power, and cost, and collaborating with hardware, software, and ML teams for effective hardware/software codesign. Responsibilities include ML workload characterization, developing architecture specifications, RTL design, and utilizing AI techniques for physical design. | Serve | 8 |
| Silicon System and Software Integration Engineer, TPU Cloud This role focuses on the integration and validation of AI/ML hardware accelerators (TPUs) for Google's cloud infrastructure. The engineer will work on ASIC development, firmware, RTL, and software integration to ensure the functionality and performance of these chips, which power Google's AI/ML applications and services. | Serve | 8 |
| Software Engineer III, AI/ML, Proxybidder ML Software Engineer III on the Proxybidder ML team at Google, responsible for the full machine learning model lifecycle including design, training, deployment, and serving in production for Google Ads. The role involves innovating on model design, analyzing experiments, enhancing model health, and collaborating with research and infrastructure teams. Requires experience with Python, C++, mathematical modeling, and ML infrastructure, with a focus on low-latency production systems. | ServePost-train | 8 |
| Software Engineer III, Vertex Inference Software Engineer III for Google Cloud's Vertex Inference team, focusing on the dataplane for serving first-party models like Gemini. The role involves implementing GenAI solutions, utilizing ML infrastructure, and optimizing performance for AI/ML capabilities within Google Cloud. | ServePost-train | 8 |
| Software Engineer III, AI/ML GenAI, Google Research Software Engineer III at Google Research focused on implementing GenAI solutions, utilizing ML infrastructure, and contributing to data preparation, optimization, and performance enhancements. The role involves core GenAI concepts like LLMs and Multi-Modal models, with experience in text, image, video, or audio generation being key. The position is primarily focused on serving AI models (L3) with a secondary involvement in post-training aspects (L2). | ServePost-train | 8 |
| Senior Engineering Manager AI Inference Platform, Distributed Cloud Senior Engineering Manager for AI Inference Platform, Distributed Cloud. Role focuses on architecting and optimizing the serving stack for models like Gemini in an on-prem cloud environment, improving speed, efficiency, and cost-effectiveness. Responsibilities include leading a team, defining technical vision for the LLM serving stack, overseeing performance analysis and benchmarking, and driving the design/implementation of advanced serving architectures. | Serve | 8 |
| Software Engineering Manager II, AI/ML GenAI, Google Cloud Compute Software Engineering Manager II for Google Cloud Compute, focusing on AI/ML GenAI. This role involves technical leadership, team management, and guiding the design and optimization of GenAI solutions, ML infrastructure, and data/model strategies. The position requires significant experience in software development, ML infrastructure optimization, technical leadership, and GenAI techniques. | ServePost-train | 8 |
| ML Chip/IP Architect, DeepMind This role focuses on defining the top-level SoC architecture and chiplet strategy for next-generation Machine Learning (ML) accelerators. The individual will lead the architecture and design of the chip top-level, manage interfaces, clocking, power, and integration of IP blocks, and architect specific accelerator components. Collaboration with micro-architecture, physical design, systems, and software teams is crucial to ensure a feasible and optimal design meeting product requirements. | Serve | 8 |
| Staff AI/ML Software Engineer, YouTube Ads Creative Foundational Infrastructure Staff AI/ML Software Engineer for YouTube Ads Creative Foundational Infrastructure. This role involves architecting, scaling, and steering next-generation infrastructure for AI/ML applications, specifically focusing on creative generation and optimization. Responsibilities include defining the technical roadmap, designing distributed systems for GenAI and media processing, building experiment and learning infrastructure, and partnering with various teams to align infrastructure with business goals. | ServeAgent | 8 |
| Senior Design and Integration Engineer, Cloud TPU The role focuses on the design, integration, and verification of Google's next-generation Tensor Processing Units (TPUs), which are custom-built accelerators for AI and machine learning workloads. The engineer will work on microarchitecture, digital logic design, and optimization for performance, power, and area, collaborating with cross-functional teams to deliver cutting-edge hardware for AI/ML applications. | Serve | 8 |
| Senior Security Engineer, AI/ML, National Security, Public Sector Senior Security Engineer focused on securing AI/ML infrastructure, particularly LLM deployments, for Google Public Sector. Responsibilities include architecting secure deployments, protecting model weights and data, mitigating AI-specific threats, and developing automated defenses. Requires experience with AI/ML development, infrastructure, containerization, and Python, along with a Top Secret/SCI security clearance. | ServeAgent | 8 |
| Senior Software Engineer, AI/ML GenAI, Google Cloud Senior Software Engineer role focused on designing and implementing GenAI solutions within Google Cloud, leveraging ML infrastructure and evaluating different techniques. Requires experience in Python/C++, ML infrastructure, software design, and state-of-the-art GenAI techniques. | ServePost-train | 8 |
| Senior Staff Software Engineer, AI/ML, Google Cloud Senior Staff Software Engineer on the AI and Infrastructure team at Google Cloud, focusing on delivering AI and Infrastructure at scale. The role involves designing, developing, and deploying large-scale software solutions, providing technical leadership, and driving ML infrastructure optimization across multiple ML areas. Requires extensive experience in ML infrastructure, design, architecture, and specific ML fields like speech/audio or reinforcement learning. | ServePost-train | 8 |
| Customer Engineer IV, AI Infrastructure, Google Public Sector Customer Engineer role focused on accelerating AI initiatives for Google Public Sector clients by owning the technical relationship with ML research teams, guiding them through solution design, accelerator selection, and ramping AI workloads onto Google's AI infrastructure. The role involves advising on hardware (GPU/TPU), ML frameworks, and model building techniques, acting as a hybrid technical and business advisor. | ServePost-train | 8 |
| Senior Applied ML Engineer, Graph Neural Network, ML Frontiers Senior Applied ML Engineer focused on Graph Neural Networks within the Graph Flow platform, bridging pioneering models with enterprise solutions. The role involves defining new features, technical leadership, literature reviews, experimentation, efficient implementation on target hardware, and productionizing components. It also includes mentoring and collaborating with clients and research partners, with a focus on applied research and engineering. | ServePost-train | 8 |
| Senior Staff Software Engineer, TPU Performance Senior Staff Software Engineer focused on optimizing ML training and serving performance on Google's TPUs. This role involves identifying and maintaining benchmarks, driving performance improvements through compiler/runtime optimizations and algorithmic innovations, and co-designing TPU-friendly models. Experience with ML infrastructure, speech/audio, or reinforcement learning is required. | ServePost-train | 8 |
| Senior TPU RTL Design Engineer, Networking, Inter-Chip Interconnects Senior engineer to design and develop RTL for Google's next-generation Tensor Processing Units (TPUs), focusing on inter-chip interconnects for AI and networking accelerators. This role involves microarchitecture, RTL design, implementation, and collaboration with system architects and verification teams to ensure high-performance, power-efficient silicon solutions for AI workloads. | Serve | 8 |
| RTL Design Engineer, Machine Learning Accelerators This role focuses on the RTL design of Machine Learning Accelerators (TPUs) for Google's AI/ML applications. The engineer will design and verify complex digital designs with a focus on TPU architecture and its integration within AI/ML-driven systems, contributing to custom silicon solutions. | Serve | 8 |
| Staff Software Engineering, YouTube ML Efficiency Staff Software Engineer focused on ML efficiency for YouTube's recommendation systems, working on optimizing models for next-gen TPUs, enabling new architectures and training procedures, and reducing complexity in the ML training and serving ecosystem through automation. | ServeData | 8 |
