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, Sound Understanding, DeepMind Research Scientist on the Sound team within Google DeepMind Frontier AI, focused on advancing research in sound understanding, joint audio-video generation, and audio editing, contributing to the next generation of generative AI technology. The role involves improving model quality, unlocking new audio capabilities, developing evaluation methods, and publishing research. | Post-trainPretrain | 10 |
| Research Scientist, Recommendation Systems, DeepMind Research Scientist at Google DeepMind focused on advancing AI development for product innovation and global challenges. The role involves driving new research ideas from conception to production, collaborating cross-functionally, and inventing novel solutions. Requires a PhD in ML/CS or equivalent experience, with a focus on LLM post-training algorithms and infrastructure using JAX. A strong publication record is preferred. |
| Post-trainShip |
| 9 |
| Senior Product Manager, Gemini Post Training, DeepMind Senior Product Manager for Gemini Post Training at Google DeepMind. This role involves guiding the post-training and evaluation process for Gemini models, translating user needs into model development priorities, and collaborating with researchers to analyze model outputs and ensure quality. The focus is on defining evaluation goals, curating evaluation suites, and investigating issues to improve model performance and readiness for release. | Post-train | 9 |
| Applied AI Engineer, Audio, XR Applied AI Engineer focused on audio for Pixel devices, bridging research and deployment in hardware-constrained environments. Responsibilities include applied research in audio ML, developing novel models for speech recognition, TTS, and enhancement, and architecting ML systems for on-device and cloud platforms. | Post-trainServe | 9 |
| Research Engineer Research Engineer at Google DeepMind focused on applying advanced ML models and research to solve real-world problems. Responsibilities include rapid prototyping, experimental design, developing scalable code, training and evaluating ML models and agents, and collaborating with research scientists and engineers. Requires a Master's degree and 2 years of experience in ML algorithm design, statistical analysis, Python/C++, and ML frameworks like TensorFlow or JAX. | Post-trainAgent | 9 |
| Senior Research Engineer Google DeepMind is seeking a Senior Research Engineer to apply AI research to high-impact problems, prototype, curate datasets, and deploy optimized ML systems. The role involves architecting and implementing scalable software libraries, driving long-term research projects, and training/evaluating deep neural models and RL algorithms. Requires a PhD or Master's degree with significant experience in ML theory, frameworks like Tensorflow/JAX/PyTorch, and leading research agendas. | Post-trainServe | 9 |
| Gemini Audio Research Scientist, DeepMind Research Scientist focused on advancing audio capabilities, particularly speech translation, by improving model quality for understanding and generation, exploring RL algorithms, and developing better evaluation methods. The role involves working with audio and visual representations and interactions, and contributing to the wider AI/ML community through publications. | Post-trainAgent | 9 |
| Senior Staff Research Scientist, Gemini Safety Post-Training, DeepMind Senior Staff Research Scientist focused on rethinking and developing safety post-training methods for agentic AI systems, particularly for Gemini models. The role involves designing and shipping post-training recipes (RL, SFT), building evaluation metrics, and translating research into production. | Post-trainAgent | 9 |
| Software Engineer III, Generative AI, Search Health Software Engineer III for Generative AI in Google Search Health, focusing on improving response quality, implementing new features, prompt engineering, and collaborating with the core model team. Responsibilities include building datasets, analyzing behavior, and running A/B experiments. Requires experience with GenAI techniques and ML infrastructure. | Post-trainAgent | 8 |
| ML Software Engineer, GenAI for Youth ML Software Engineer focused on building scalable, responsible AI frameworks for youth-focused products. The role involves developing unified infrastructure, algorithmic steering, and automated validation layers to bridge foundational research with production environments, operating across global product lines and acting as a technical advisor. | Post-trainServe | 8 |
| Senior Staff Engineering Analyst Manager, Gemini, NanoBanana, Veo Senior Staff Engineering Analyst Manager for Gemini, NanoBanana, and Veo, focusing on AI model mitigations and post-training. This role involves leading a team, pioneering safety technologies, driving cross-functional alignment, directing launch strategies for foundational models, and applying data science to audit model safety and uncover vulnerabilities. | Post-train | 8 |
| Software Engineer Software Engineer at Google DeepMind focused on applying research to build next-generation GenAI features. Responsibilities include prototyping GenAI solutions, curating datasets, building ML pipelines for generative media and multimodal understanding, developing product code, and performing comprehensive testing. Requires experience in developing ML models with Tensorflow/PyTorch/JAX and applying ML/statistics/diffusion model theory. | Post-trainData | 8 |
| Software Engineer Software Engineer at Google DeepMind focused on applying research to high-impact problems by prototyping GenAI solutions, curating datasets, and building ML pipelines for generative media, multimodal understanding, and reinforcement learning. Requires experience in ML, software development, data structures, algorithms, and ML infrastructure management. | Post-trainData | 8 |
| Software Engineer Software Engineer at Google DeepMind focused on applying research to high-impact problems by prototyping GenAI solutions, curating datasets, and building ML pipelines for generative media, multimodal understanding, and reinforcement learning. Requires experience in training generative AI models, developing ML models with frameworks like Tensorflow/PyTorch/JAX, ML infrastructure management, and software development. | Post-trainData | 8 |
| Software Engineer Software Engineer at Google DeepMind focused on applying research to high-impact GenAI problems, including prototyping solutions, curating datasets, and building ML pipelines for generative media, multimodal understanding, and reinforcement learning. The role involves developing robust product code, performing comprehensive testing, collaborating with peers, resolving system issues, creating documentation, and managing the full deployment lifecycle. | Post-trainData | 8 |
| Software Engineer, PhD, Early Career, AI/Machine Learning, 2026 Start Google is seeking PhD graduates for Software Engineer roles focused on AI/Machine Learning. The role involves developing and deploying advanced ML systems across the full stack, from hardware acceleration to production APIs, and transforming research expertise into scalable products. The position requires experience in ML/AI and coding, with a preference for large-scale distributed environments and deep learning frameworks. | Post-trainServe | 8 |
| Software Engineer III, Perception, XR Software Engineer III, Perception, XR at Google, focusing on on-device deep learning for audio enhancement and speech understanding in smart wearable glasses. The role involves developing and evaluating speech enhancement algorithms, experimenting with ML modeling, and acquiring data for training models. | Post-trainData | 7 |
| Business Data Scientist, Customer Voice, Analytics This role focuses on developing and deploying NLP and machine learning models to extract insights from customer conversations for a Go-to-Market team. It involves identifying trends, predicting customer behaviors, and ensuring statistical rigor in reporting, with a focus on Large Language Models and prompt engineering. | Post-trainData | 7 |
| Senior Software Engineer, Motion Algorithms Senior Software Engineer focused on developing and productizing cutting-edge ML models and algorithms for motion and location systems on Android devices and Pixel products. The role involves working on sensor fusion, state estimation, and optimizing these for resource-constrained environments, impacting core features and user experiences. | Post-trainServe | 7 |
| Engineering Manager, Ads ML Modeling Engineering Manager for Google's Ads ML Modeling team, responsible for building and maintaining models to improve advertiser campaign optimization. The role involves people management, technical leadership, strategic planning, and driving the development of ML applications, data analyses, and methodologies. Focuses on areas like forecasting, predictive caching, and UI ranking models. | Post-train | 7 |