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 |
|---|---|---|
| Software Engineer III, GenAI Data Operations Research, XR Software Engineer III role focused on GenAI Data Operations Research for XR and Platforms & Devices. Responsibilities include leading synthetic dataset deliveries, building toolkits for GenAI inference and metadata extraction, and developing pipelines for fine-tuning foundational models. Requires experience in software development, ML infrastructure, and data processing, with a focus on speech/audio, reinforcement learning, or other ML specializations. | DataPost-train | 8 |
| AI/ML Senior Software Engineer, Data Optimization and Platform This role focuses on improving the time to model quality for users by applying data optimization techniques through integrated tools and platforms. The engineer will scale data optimization techniques, establish technical relationships with product areas, leverage Google Research assets, and collaborate with Research teams and ML practitioners to build and iterate on engineering tools, processing pipelines, and data optimization techniques. The goal is to make AI helpful for everyone by advancing Google's AI capabilities. |
| DataPost-train |
| 8 |
| Software Engineer, AI/ML, PhD, Early Career Software Engineer role focused on scaling data optimization techniques to improve ML model performance and quality, working with Research teams and ML practitioners to build and iterate on engineering tools and processing pipelines. The role emphasizes the data-centric nature of AI in the Gemini era and improving model quality through data optimization. | Data | 8 |