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 |
|---|---|---|
| Research Scientist, Generative AI, DeepMind Research Scientist at Google DeepMind focused on designing and developing novel generative methodologies, particularly diffusion models, for media synthesis and scientific discovery. The role involves collaborating with international teams, utilizing advanced deep learning techniques, and contributing to the advancement of AI for public benefit and product innovation. | Post-trainPretrain | 10 |
| Research Engineer, Responsibility Engineering, DeepMind Research Engineer at Google DeepMind focused on AI safety, developing post-training strategies to mitigate adversarial risks and building evaluation infrastructure for frontier language models. The role involves prototyping scalable engineering solutions, optimizing training and inference pipelines, and collaborating with research scientists to translate safety research into implementations. |
| 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 |