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 |
|---|---|---|
| Staff Software Engineer, AI/ML Recommendations, Rankings, Predictions, YouTube Staff Software Engineer at Google working on AI/ML for YouTube Recommendations, Rankings, and Predictions. The role involves designing, developing, and deploying large-scale software solutions, providing technical leadership, and optimizing ML infrastructure. Key responsibilities include leading the design and implementation of recommendation systems, optimizing ML infrastructure, and guiding model architecture development. Requires significant experience in building and deploying recommendation systems models in production and leading ML design and optimization. | ShipAgent | 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, AI/ML Recommendations, Rankings, Predictions, YouTube Software Engineering Manager II for AI/ML Recommendations, Rankings, and Predictions at YouTube. This role involves leading a team of engineers, setting team priorities, developing technical roadmaps, designing and implementing recommendation systems, optimizing ML infrastructure, and guiding model architecture development. Requires experience in software development, ML design, ML infrastructure optimization, building and deploying recommendation systems, and technical/people leadership. | ShipServe | 7 |
| Senior Software Engineer, AI/ML Recommendations, Rankings, Predictions, YouTube Senior Software Engineer focused on building and deploying recommendation systems models for YouTube, leveraging ML infrastructure and contributing to architecture design. This role involves coding, testing, debugging, and designing models for retrieval, prediction, ranking, and personalization. | ShipData | 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 |
