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, AI/ML, LLM Modeling This role focuses on training and deploying Large Language Models (LLMs) for search applications, involving reinforcement learning, multi-step reasoning, distillation, and optimizing model latency in production. The engineer will propose new modeling ideas, collect and evaluate training data, design evaluations, and collaborate on applying LLMs in real-world scenarios. | Post-trainServe | 9 |
| Research Software Engineer, Generative AI Research Software Engineer focused on developing foundational models and core technologies for synthesizing reality, particularly human body, face, and related components, to power machine learning, build better products, and enable next-generation user experiences, with applications in AR and XR devices. The role involves developing algorithms for 3D body shape estimation, rigging, skinning, and physics-based generative animation conditioned on multimodal inputs, with a requirement for publication in AI conferences. |
| Post-trainServe |
| 9 |
| Visiting Faculty Researcher, AI Personalization Visiting Faculty Researcher at Google focusing on AI Personalization. The role involves proposing novel ideas for models that learn continuously from user interactions, adapt with minimal data, and deploy efficiently on personal devices. This research position emphasizes contributing to the academic community through publications and collaborating on research proposals, while also influencing product development with potential applications in generative AI, prompt engineering, and personalization. | Post-trainAgent | 9 |
| Software Engineer III, 3D Modelling, XR Google is seeking a Machine Learning Engineer with a focus on 3D geometry to work on the convergence of AI and XR. The role involves managing the end-to-end training process for ML models, optimizing them for various environments, and ensuring data quality and robustness. The engineer will adapt research in monocular depth modeling for real-world scenarios, bridging the gap between research and product requirements. | Post-trainServe | 8 |
| Software Engineer III, Machine Learning, Search Intelligence Software Engineer III, Machine Learning, Search Intelligence at Google, focused on developing and deploying core ranking and machine learning models for Google Search. The role involves building data pipelines, contributing to model distillation, and maintaining training infrastructure to improve performance for challenging queries, particularly for long-tail query scenarios. The position requires experience in software development, ML infrastructure, and potentially speech/audio, reinforcement learning, or other ML specializations. | Post-trainServe | 8 |
| Senior Applied ML Engineer, Graph Neural Network, ML Frontiers Senior Applied ML Engineer focused on Graph Neural Networks within the ML Frontiers team, collaborating on LLM agents and decision forests. The role involves feature development, research exploration, and client collaboration, bridging pioneering models with enterprise solutions. | Post-train | 8 |
| Software Engineer III, AI/ML, YouTube Shopping Google is seeking a Software Engineer III, AI/ML for their YouTube Shopping team in Zurich. The role involves designing, implementing, and deploying ML models for tasks like Product Detection and Video Classification, building training data pipelines, and ensuring model performance through evaluation frameworks. The engineer will also contribute to the back-end infrastructure for efficient model serving at scale and implement solutions in specialized ML areas. | Post-trainServe | 8 |
| Software Engineer III, YouTube Streaming Trust and Safety Software Engineer III at Google YouTube, focusing on Trust and Safety for livestreams. The role involves analyzing content gaps, building multi-modal classifiers (video, image, audio, transcripts, metadata) using machine learning, and productionizing these solutions. Requires experience in applied ML, Python, and handling large-scale systems. | Post-train | 7 |
| Software Engineer III, YouTube Trust and Safety Software Engineer III at Google's YouTube Trust and Safety team, focusing on building classifiers and applying ML methods to improve automatic content detection and address trust and safety challenges. The role involves analyzing content understanding gaps, orchestrating signals from expert models, and productionizing ML solutions. | Post-trainServe | 7 |