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 |
|---|---|---|
| Software Engineering Manager, GPU AI Infrastructure Software Engineering Manager responsible for leading a team that develops system software and networking technologies for GPU-based AI/ML supercomputers in Google's data centers. This includes managing engineers, defining technical roadmaps, and overseeing the integration, testing, deployment, and debugging of system software for accelerator products. | Serve | 7 |
| Software Engineering Manager, Emergent AI infrastructure Team Software Engineering Manager for an Emergent AI infrastructure team focused on building next-generation on-premises AI infrastructure, integrating hardware to software design, workload management, and large-scale AI clusters. The role involves technical leadership, people management, and overseeing the deployment of large-scale projects. | Serve |
| 7 |
| Staff Software Engineer, TPU Machine Learning Supercomputer Staff Software Engineer role focused on designing and developing system software for TPU Machine Learning Supercomputers, improving scalability and reliability of large-scale software across distributed hardware. The role involves working on various software layers, from host daemons to network routing, and developing analytics for managing ML systems. Experience with C++, Go, distributed systems, and ML applications is required. | Serve | 7 |
| Software Engineer Manager II, Embedded Systems/Firmware, Silicon This role manages a team of compiler engineers focused on optimizing AI models for EdgeTPU hardware. Responsibilities include improving compiler quality and performance, developing parallelization and scheduling algorithms for ML workloads, and mapping AI models to hardware instructions. The role requires experience in compiler development, ML accelerators, and people management. | Serve | 7 |
| RTL Design and Integration Engineer, TPU and ML This role focuses on the RTL design and integration of Google's Tensor Processing Units (TPUs), which are custom hardware accelerators for AI/ML workloads. The engineer will be responsible for microarchitecture, design, implementation, and integration of digital logic blocks, collaborating with cross-functional teams to deliver hardware. The role emphasizes optimizing for performance, power, and area in complex digital designs for AI accelerators. | Serve | 7 |
| Software Engineer III, AI/ML Computer Vision, AR Software Engineer III at Google working on AI/ML Computer Vision for AR. Responsibilities include writing product/system code, collaborating with peers, contributing to documentation, triaging issues, and implementing computer vision solutions with ML infrastructure, model optimization, and data processing. Requires a Bachelor's degree, 2 years of Python/C++ experience, 1 year of Computer Vision experience, and 1 year of ML infrastructure experience. | ServeData | 7 |
| Software Engineer III, AI/ML, Google Cloud Software Engineer III on the AI and Infrastructure team at Google Cloud, focusing on delivering AI and Infrastructure at scale. Responsibilities include writing product/system code, collaborating on design/code reviews, contributing to documentation, triaging/debugging issues, and implementing solutions in specialized ML areas, utilizing ML infrastructure, and contributing to model optimization and data processing. | Serve | 7 |
| Software Engineer III, AI/ML, Google Ads Software Engineer III role within Google Ads focusing on implementing ML solutions, utilizing ML infrastructure, and contributing to model optimization and data processing. Requires experience in programming (Python/C++) and ML infrastructure, with a specialization in areas like speech/audio, reinforcement learning, or other ML fields. | Serve | 7 |
| Software Engineer III, AI/ML, AI and Infrastructure Software Engineer III on the AI and Infrastructure team at Google, focusing on delivering AI and Infrastructure at scale. Responsibilities include writing code, collaborating on design and code reviews, triaging issues, and implementing ML solutions with a focus on ML infrastructure, model optimization, and data processing. Requires experience in Python/C++, ML infrastructure, and a specialization in areas like speech/audio or reinforcement learning. | ServeData | 7 |
| Staff Software Engineer, Machine Learning Compilers, Edge TPU Staff Software Engineer focused on building ML compilers for EdgeTPU hardware, optimizing ML models for inference, and working on hardware/software co-optimizations. Collaborates with ML model developers and researchers to deploy models on EdgeTPU. | Serve | 7 |
| Staff Software Engineer, TPU Performance Staff Software Engineer focused on optimizing the performance and efficiency of Google's TPU fleet for Machine Learning training and serving workloads, including models like Gemini. This role involves deep analysis of performance metrics, collaboration with product teams and researchers, and implementation of solutions at scale, potentially touching compiler, runtime, model co-design, quantization, and sparsity. | ServePost-train | 7 |
| Software Engineer, AI/ML Software Engineer role focused on implementing ML solutions, utilizing ML infrastructure, and contributing to model optimization and data processing. Requires experience in software development and ML infrastructure, with preferred qualifications in C++ and software design. | Serve | 7 |
| Software Engineer III, AI/ML, Google Cloud Software Engineer III on the AI and Infrastructure team at Google Cloud, focusing on delivering AI and Infrastructure at scale. The role involves writing product/system code, collaborating on design and code reviews, contributing to documentation, triaging and debugging issues, and implementing solutions in ML areas including ML infrastructure, model optimization, and data processing. Requires experience in Python/C++, ML infrastructure (deployment, evaluation, optimization, data processing), and optionally speech/audio or reinforcement learning. | Serve | 7 |
| Senior Software Engineer, AI/ML, YouTube Senior Software Engineer at Google's YouTube, focusing on AI/ML development. The role involves writing and testing code, collaborating with stakeholders, contributing to documentation, triaging and debugging issues, and designing/implementing solutions in specialized ML areas using ML infrastructure. Requires experience in Python, C++, software design, and specific ML fields like speech/audio, reinforcement learning, or ML infrastructure. | Serve | 7 |
| Senior Software Engineer, Machine Learning, Google Cloud Compute Senior Software Engineer on Google Cloud Compute focusing on ML/AI algorithms, deep learning, and NLP. Responsibilities include software development, design, testing, deployment, and maintenance, with a focus on managing project priorities and deliverables. Requires 5 years of software development experience and 3 years of experience with ML/AI algorithms and tools. | Serve | 7 |
| Software Engineer, TPU Compiler, PhD, Early Careers Software Engineer role focused on developing and optimizing the TPU compiler for large-scale machine learning models. This involves writing C++ code, designing performance optimizations, and applying AI techniques to the compiler itself. The role supports both internal Google teams (like DeepMind) and external Google Cloud customers. | Serve | 7 |
| Senior Software Engineer, GPU Performance Senior Software Engineer focused on optimizing GPU performance for Google's AI models and products. This role involves low-level GPU programming, compiler optimizations, and influencing the GPU software stack and fleet deployment to ensure top performance for ML workloads. | Serve | 7 |
| Software Engineer III, AI/ML, YouTube Software Engineer III, AI/ML role at Google YouTube, focusing on implementing ML solutions, utilizing ML infrastructure, and contributing to model optimization and data processing. Requires experience in Python/C++, ML infrastructure, and potentially speech/audio or reinforcement learning. | Serve | 7 |
| Software Engineer III, AI/ML, Google Cloud AI Software Engineer III on the Google Cloud AI Research team, focusing on implementing ML solutions, utilizing ML infrastructure, and contributing to model optimization and data processing. The role involves writing product/system development code, collaborating with peers, triaging issues, and debugging. Requires experience in Python/C++, and ML infrastructure such as model deployment, evaluation, optimization, and data processing. Experience with speech/audio or reinforcement learning is a plus. | Serve | 7 |
| Hardware Architecture Modeling Engineer, PhD, University Graduate This role focuses on developing architectural and micro-architectural models for next-generation TPUs (Tensor Processing Units) to enable quantitative analysis of performance and power. The engineer will contribute to Machine Learning workload characterization, benchmarking, and hardware-software co-design, collaborating with various teams to define TPU chip specifications and roadmaps for AI/ML hardware acceleration. | Serve | 7 |
| Software Engineer, PhD, Early Career, 2026 Google is seeking a PhD Software Engineer with expertise in AI/ML and large-scale distributed systems to design, test, deploy, and maintain software solutions for AI and Infrastructure (AI2) organization. The role involves defining technical goals, developing scalable systems, applying research expertise to complex problems, and contributing to essential Google services and Cloud products. | Serve | 7 |
| Design Verification Engineer, PhD, Early Career This role focuses on the design and verification of AI/ML hardware accelerators (TPUs), involving architecture definition, performance modeling, RTL design, and hardware/software co-design. The engineer will work on optimizing ML workloads and developing efficient design verification strategies for next-generation TPUs, leveraging AI techniques for physical design convergence. | Serve | 7 |
| Software Engineering Manager II, Google Cloud Software Engineering Manager II for Google Cloud's AI and Infrastructure team, focusing on delivering AI and Infrastructure at scale. The role involves technical leadership, team management, setting priorities, developing roadmaps, and guiding system designs, with a focus on enabling advanced AI models and delivering computing power. | Serve | 7 |
| Software Engineer, PhD, Early Career, Campus, 2025 Start Software Engineer with a PhD, focusing on AI/ML infrastructure and systems within Google Cloud. The role involves writing product/system development code, participating in design reviews, reviewing code, contributing to documentation, triaging and debugging complex technical issues, and collaborating on design, analysis, and development across the stack. The focus is on building and scaling AI/ML capabilities on Google's frameworks and infrastructure, contributing to products used by billions. | Serve | 7 |
| Software Engineer, Early Careers, PhD, Cloud AI Software Engineer role focused on implementing and designing Search features, leveraging advanced GenAI capabilities and LLM concepts, with a focus on Kubernetes-based infrastructure for scalability and performance. | Serve | 7 |
| Software Engineer, Systems Research, PhD, Early Career Google is seeking a Software Engineer for Systems Research with a PhD to explore emerging technologies and systems, design and build prototypes for data center and cloud environments including machine learning, and influence products by operating across research and engineering teams. | Serve | 7 |
| Graphics/Machine Learning Hardware IP Silicon Architect This role focuses on architecting and integrating custom silicon solutions for Google's consumer products, specifically targeting hardware IP for Graphics, Multimedia, and Machine Learning acceleration. The individual will collaborate with software and hardware teams to define and deliver ASIC IP architectures that meet power, performance, and area targets, from initial design through to product launch. Experience with low-power ASIC hardware IP for complex SoCs, particularly in Graphics Processing and Machine Learning Acceleration, is preferred. | Serve | 5 |
| Software Engineer II, Infrastructure Software Engineer II, Infrastructure role focused on building and maintaining Kueue, a Kubernetes scheduler for AI/ML workloads, managing accelerators like TPUs and GPUs. The role involves algorithm design, system performance, and Kubernetes internals, collaborating with internal and external AI partners and the open-source community. | Serve | 5 |
| Platform Technical Leader, Statera This role is for a Platform Technical Leader focused on load balancing infrastructure for AI workloads, connecting AI models and agents. The responsibilities include driving data plane performance, optimizing scalability, advocating for GKE, expanding network protocols (IPv6, HTTP/3), and strengthening DoS protection. The role requires significant experience in C++, software development, large-scale infrastructure, and distributed systems, with a focus on technical leadership. | Serve | 5 |
| Software Engineer III, Ads Campaign Automation (Mandarin) Software Engineer III role focused on Ads Campaign Automation, involving large-scale experiments for Ads serving, bidding models, and retrieval systems. Requires strong software development skills, data-driven approaches, and collaboration with cross-functional teams. Familiarity with GenAI concepts is preferred. | Serve | 5 |
| Software Engineer, Ads Campaign Automation (Mandarin) Software Engineer role focused on Ads Campaign Automation, involving large-scale experiments for ads serving, bidding models, and retrieval systems. Requires experience with ads buying platforms, campaign automation, optimization, and performance diagnosis within the ads ecosystem. Fluency in Mandarin is essential for regional collaboration. | Serve | 5 |
| Software Engineering Manager II, Google Cloud Software Engineering Manager II for Google Cloud's AI and Infrastructure team, focusing on leading engineers, setting team priorities, developing technical roadmaps, and guiding system designs for large-scale AI and infrastructure projects. The role involves people management and technical leadership within a team that supports Google's AI models and computing power. | Serve | 5 |
| Software Engineer, TPU Software Systems, Cloud Software Engineer role focused on designing, developing, and maintaining the software infrastructure for Google's TPU supercomputers, specifically tailored to support massive-scale machine learning applications and enable efficient execution of data parallelism algorithms. | Serve | 5 |
| Staff Site Reliability Engineer Staff Site Reliability Engineer for Google Cloud's AI infrastructure, focusing on the reliability and supportability of data intelligence systems (Woodshed and Napa) that underpin Google's AI initiatives. The role involves leading the SRE team, improving system design, automation, and capacity management for large-scale, distributed systems, with a specific emphasis on production ML systems. | Serve | 5 |
| Staff Software Engineer, ML Fleet Systems Staff Software Engineer role focused on building and providing technical leadership for ML Fleet Systems, which involves general software engineering tasks like coding, testing, deploying services, and operational support for AI and Infrastructure teams at Google. The role contributes to the development of AI models and computing power at scale. | Serve | 5 |
| RTL Design Engineer, Google Cloud, Silicon The role involves designing and implementing ASICs to accelerate machine learning computation in data centers, specifically for Google's AI platform (Vertex AI) and TPUs. The engineer will focus on microarchitecture, implementation, and collaboration with various hardware and software teams to deliver high-performance, efficient, and reliable silicon solutions. | Serve | 5 |
| Cloud Data and AI Engineer, Professional Services This role focuses on guiding Public Sector customers in developing, configuring, and deploying data and AI solutions on Google Cloud Platform. It involves providing architecture guidance, best practices, data migration, and troubleshooting for ML models and integrations. The engineer will also consult on optimal data and AI solution design and travel to customer sites for deployment and workshops. | ServeData | 5 |
| Staff Software Engineer, Google Cloud Storage, AI/ML Staff Software Engineer on the Google Cloud Storage AI/ML Solutions team, focusing on building storage solutions for AI/ML workloads, from training to inference. The role involves designing, implementing, and optimizing high-complexity features for scalable and performant storage systems that cater to the specific demands of AI/ML. | Serve | 5 |
| Senior Software Engineer, Vertex 1P GenAI SRE This role focuses on ensuring the reliability, scalability, and performance of Google's Vertex AI Generative AI platform, which serves both internal teams and Google Cloud customers. The Senior Software Engineer will be responsible for improving system architecture, resolving outages, and driving production excellence using SRE principles. | Serve | 5 |
| Staff Software Engineer, Enterprise Product Strategy and Architecture Staff Software Engineer focused on defining and scaling enterprise-wide architectural standards, reference models, and patterns for data platforms and AI/ML capabilities within Google's Corporate Engineering. The role involves technical design consultations, architecture reviews, supporting the Enterprise Architecture Board, leading technical forums, and establishing reusable patterns for data ingestion, pipeline orchestration, model deployment, and generative AI integrations. The goal is to ensure alignment with long-term data scalability and enterprise AI safety, reduce redundancy, and accelerate delivery. | ServeData | 5 |
| Eye Tracking Systems Staff Software Engineer Staff Software Engineer for Google's XR Perception team, focusing on eye tracking systems for AR/VR. The role involves technical leadership, algorithm design, and software development for compute-constrained Android devices, with an emphasis on integrating generative AI and LLM interfaces into workflows. | Serve | 5 |
| Staff Embedded Software Engineer, Audio/Firmware Staff Embedded Software Engineer for Google's Android microXR project, focusing on audio firmware for AR smart glasses. The role involves developing and optimizing audio systems, integrating with ML teams, and supporting AI-driven use cases within an embedded, real-time context. | Serve | 5 |
| Software Engineer III, Embedded Systems, Hearables Audio software Software Engineer III on the Pixel Hearables Audio Software team, responsible for developing next-generation Google Pixel earbuds. This role involves productizing novel audio algorithms that combine signal processing, acoustics, and machine learning, working with early hardware prototypes to design and implement new features. The position requires contributions to audio system architecture, implementation and integration of audio software for hearable devices and phones, and developing infrastructure to support algorithmic development and scale engagement with research teams. Collaboration with product managers, UX, and hardware counterparts is essential. | Serve | 5 |
| Senior Software Engineer, Android CI Infrastructure Senior Software Engineer to build next-generation, AI-powered infrastructure supporting Continuous Integration (CI) systems for Android, Chrome, and ChromeOS. The role involves designing, implementing, and deploying scalable and reliable systems, with a focus on streamlining operational workflows using Agentic AI and enhancing system reliability. The engineer will also contribute to AI accelerated development and ensure the scalability and availability of infrastructure. | Serve | 5 |
| Software Engineer III, Infrastructure, AI and Infrastructure Software Engineer III on the AI and Infrastructure team at Google, focusing on building and scaling the infrastructure that powers AI models and services. The role involves writing product/system development code, participating in design reviews, reviewing code, contributing to documentation, and triaging/debugging system issues. Requires experience in C++, Python, or Go, and large-scale infrastructure/distributed systems. Preferred qualifications include a Master's/PhD, performance analysis, and data structures/algorithms. | Serve | 5 |
| Software Engineer, Performance, Reliability, Observability, PhD, Early Career Software Engineer role focused on performance, reliability, and observability tools for Google Cloud control plane systems. The role involves analyzing VM performance, developing performance models, designing benchmarks, and exploring the use of machine learning for anomaly detection. While the core is engineering and performance analysis, there's an exploration component involving ML for anomaly detection. | Serve | 5 |