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.
Currently tracking 498 active AI roles, down 12% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $98k–$1030k (avg $233k).
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 |
|---|---|---|
| Research Scientist, AQUA, DeepMind Research Scientist at DeepMind India focused on developing foundational capabilities in Large Models for Artificial General Intelligence (AGI) by advancing autonomous agents through reinforcement learning and ML optimization methods. The role involves designing, implementing, and evaluating models and agents, pushing the boundaries of RL, and collaborating with Responsible AI teams. Requires a PhD, experience with ML frameworks, deep learning, RL, and a publication record. | AgentPost-train | 10 |
| AI Research Scientist, Applied AI, Google Cloud Research Scientist role focused on designing, developing, and deploying agentic AI solutions for enterprise use cases within Google Cloud's Applied AI division. The role involves taking ownership of AI quality, implementing and advancing AI techniques, and driving progress through experimentation. It requires a PhD, experience leading research, and applied ML experience, with a focus on enterprise AI solutions and collaboration with model builders. |
| AgentPost-train |
| 9 |
| Staff AI Research Scientist, Applied AI, Google Cloud Staff AI Research Scientist role focused on designing, developing, and deploying scalable and agentic AI solutions for enterprise use cases within Google Cloud's Applied AI team. The role involves taking ownership of AI quality for production systems, implementing evaluation frameworks, and advancing AI techniques through experimentation. It requires a PhD, experience with ML algorithms and LLMs, and a publication record, with a focus on applied research and product contribution. | AgentEval Gate | 9 |
| Research Scientist, Memory, Reasoning and Continual Learning, DeepMind Research Scientist at Google DeepMind focused on advancing AI in Memory, Reasoning, and Continual Learning. The role involves initiating novel research, designing and executing experiments on topics like RAG, continual learning, and multi-step reasoning, developing evaluations for complex capabilities, and building infrastructure for advanced AI systems. The position requires a PhD and experience in AI research, with a focus on publishing findings and contributing to the research community. | AgentPost-train | 9 |
| Research Engineer, Frontier Safety Mitigations, DeepMind Research Engineer focused on developing and deploying advanced safety mitigations for frontier AI models, specifically defending against misuse in domains like Cybersecurity and CBRNE. The role involves building classifiers, data pipelines, monitoring systems, and evaluating agentic AI systems, with a strong emphasis on automated red-teaming and adversarial robustness. | AgentEval Gate | 9 |
| Research Engineer, Frontier Safety Mitigations, DeepMind Research Engineer focused on frontier AI safety mitigations, defending against misuse domains like CBRNE and Harmful Manipulation. Responsibilities include building evaluations, red-teaming, deploying in-model and out-of-model mitigations, and monitoring risks for frontier models, particularly agentic AI systems. The role involves developing classifiers, monitoring systems, and advancing research in automated red-teaming and adversarial robustness. | AgentEval Gate | 9 |
| Research Scientist, Robotics, DeepMind Research Scientist at Google DeepMind Robotics focused on building foundation models like vision-language-action (VLA) models for physical agents, enabling robots to perceive, plan, think, use tools, and act. The role involves research into agentic reasoning, real-world understanding, and robot control, with a focus on publishing research and contributing to the AI research community. | AgentPost-train | 9 |
| Research Engineer, Embodied Agents, DeepMind Research Engineer at DeepMind focused on building AI agents that operate in physical environments, advancing physical AGI. The role involves designing learning infrastructure, collaborating with partners for deployment, and building developer tools for robotics capabilities. Key challenges include bridging the gap between simulation and real-world robot performance. | AgentServe | 9 |
| Research Engineer, Multi Agent Learning, DeepMind Research Engineer at Google DeepMind focused on developing novel multi-agent learning algorithms and frameworks. The role involves building and maintaining large-scale simulation platforms and research pipelines on cutting-edge infrastructure, partnering with Research Scientists to translate research into production-quality code, and optimizing the research workflow. Requires experience in deep learning frameworks, Python/C++, and distributed training on accelerators. A PhD in ML, RL, or Multi-Agent Systems and experience with language models are preferred. | AgentPost-train | 9 |
| Research Scientist, Manipulation for Robotics, DeepMind Research Scientist role focused on pioneering AI integration into robotics for physical agents, enabling robots to perceive, plan, think, use tools, and act. The role involves developing and training large foundation models for general-purpose dexterous manipulation tasks, aiming for human-level performance on real-world applications using frontier robotics models. This includes working with simulators, real robots, and various AI techniques like reinforcement learning and vision-language-action models. | AgentData | 9 |
| Senior Research Scientist, App and Ecosystem Trust Research Scientist role focused on Android security and AI agent safety, developing and publishing novel research, designing neuro-symbolic and agent-powered systems for threat detection, and using machine learning for code analysis to combat malware and evasion techniques within the Android ecosystem. | Agent | 8 |
| Research Software Engineer, Computer Vision Research Software Engineer focused on computer vision and ML for XR applications, specifically 3D reconstruction, scene understanding, and novel view synthesis. The role involves research, development, and optimization of 3D scene representation pipelines, bridging the gap from research to product. | AgentServe | 8 |
| Staff Research Scientist, App and Ecosystem Trust Research Scientist role focused on protecting Android users from abusive apps by developing and publishing novel research on Android security and AI agent safety. The role involves designing neuro-symbolic and agent-powered systems, and using machine learning for malware detection and evasion technique neutralization. | Agent | 8 |