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 592 new AI-related roles. That is a +32% change versus the prior 30 days (448 → 592).
| 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, 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 |
| Post-Doctoral Researcher, PhD, 2026 Start, DeepMind (Fixed-Term Contract) - Post-Doctoral Researcher at Google DeepMind focusing on pushing the frontiers of AI by identifying impactful problems, designing novel algorithms, and demonstrating their effectiveness at scale. The role involves conducting research, publishing high-quality work, and contributing to production-ready systems using frameworks like JAX. Expertise in machine learning fundamentals, foundational models, reinforcement learning, generative modeling, and causal inference is central to the team's work. | Pretrain | 10 |
| Research Scientist, Frontier AI, DeepMind Research Scientist at Google DeepMind focused on advancing the frontiers of artificial intelligence, specifically developing next-generation multimodal models. This role involves defining and leading ambitious research projects, designing innovative model architectures, and contributing to the overall research strategy with a strong emphasis on publications in top ML conferences. | PretrainPost-train | 10 |
| Senior Research Scientist, Google Research Research Scientist at Google Research focused on fundamental research and innovation in AI/ML, including machine learning, deep learning, data mining, NLP, and core search. The role involves setting up large-scale tests, deploying ideas, publishing findings, and contributing to the wider research community. Requires a PhD and experience leading research agendas with publication submissions. | Pretrain | 10 |
| Staff Software Engineer, BigQuery Agentic AI Staff Software Engineer at Google BigQuery focused on building agentic AI solutions for data processing. The role involves designing and developing systems that integrate LLMs with BigQuery, architecting agents for reasoning over large datasets, optimizing pipelines, and contributing to agentic frameworks with tool use and evaluation. This position is at the intersection of distributed systems and generative AI. | Agent | 9 |
| Forward Deployed Engineer II, GCC Forward Deployed Engineer II, GCC role focused on embedding with customers to build, deploy, and productionize bespoke agentic AI solutions using Google Cloud's AI portfolio. Responsibilities include architecting integrations, developing agentic workflows, building evaluation and observability pipelines, and providing feedback to product teams. Requires experience in software development, ML, NLP, generative AI agents, and DevOps, with preferred experience in multi-agent systems and LLM optimization. | AgentEval Gate | 9 |
| Senior Software Engineer, DeepMind Senior Software Engineer at Google DeepMind focused on building and enhancing serving solutions for Gemini models, developing new infrastructure for advanced capabilities like streaming and audio logic, and ensuring model quality in production. The role involves driving technical vision and roadmap for the team. | ServeAgent | 9 |
| Forward Deployed Engineer III, GCC (French, German) Google Cloud is seeking a Forward Deployed Engineer III to build and deploy agentic AI solutions for enterprise customers. This role involves bridging the gap between frontier AI products and production-grade reality, architecting and coding connective tissue, and building evaluation pipelines and observability frameworks. The engineer will also act as a product catalyst by identifying friction points and converting them into product feature requests. The role requires experience in designing and deploying NLP models and Generative AI agents, implementing MLOps pipelines, and building generative AI solutions in a customer-facing capacity. | AgentEval Gate | 9 |
| Senior Software Machine Learning Engineer, DeepMind Senior Software Machine Learning Engineer at Google DeepMind focused on building and testing advanced AI agents. Responsibilities include creating agentic workflows, engineering runtime infrastructure for LLMs, partnering with researchers, and designing evaluation frameworks. The role involves working with Gemini models, testing on robots, and ensuring production reliability. | Agent | 9 |
| Forward Deployed Engineer III, Applied AI, Google Cloud Forward Deployed Engineer III, Applied AI, Google Cloud. Role focuses on transforming conversational AI prototypes into production-ready, end-to-end engineered solutions for customers. This involves leading technical delivery for Conversational AI pilots, architecting and coding agentic workflows, building evaluation pipelines and observability frameworks, and ensuring customer success with Google's AI portfolio and Vertex AI platform. Requires strong software engineering, MLOps, and cloud infrastructure skills, with an emphasis on multi-agent systems, RAG, and optimizing inference. | AgentServe | 9 |
| 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 |
| 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 |
| 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 |
| Threat Modeler Lead, CBRNE, DeepMind Lead threat modeler for AI safety in CBRNE domains, focusing on evaluating and mitigating dual-use risks of advanced AI models. This role involves refining threat modeling frameworks, designing evaluations for AI risks, collaborating with mitigation teams, and engaging with external stakeholders. Requires a PhD and experience in national labs or defense organizations, with a preference for experience in red-teaming LLMs and understanding CBRNE risks. | Eval Gate | 9 |
| Software Engineer, Applied AI Software Engineer, Applied AI at Google, focusing on deploying and maintaining production-grade AI agents for Gemini Enterprise. Responsibilities include prompt engineering, fine-tuning, CI/CD, and monitoring agent performance. Requires experience with generative AI agents, ML infrastructure, and potentially speech/audio or reinforcement learning. | AgentPost-train | 9 |
| Engineering Manager, ML Performance Engineering Manager for Google's TPU Performance team, focusing on optimizing the speed and efficiency of AI/ML model training and inference on custom TPU hardware. The role involves leading a team to develop and maintain ML benchmarks, identify performance opportunities, drive optimizations (near-term and out-of-the-box), and participate in algorithmic innovations and co-designing TPU-friendly models. This includes work on inference serving, quantization, and compiler optimizations, serving both internal Google teams and external AI companies. | ServePost-train | 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 Scientist, Gemini Data, DeepMind Research Scientist/Engineer at Google DeepMind focused on expanding Gemini pre-training models for legal, finance, and healthcare domains. Responsibilities include designing evaluation protocols, proposing novel data solutions, and executing experiments to improve model capabilities. Requires PhD, 2 years LLM modeling experience, and ML/AI publications. | PretrainPost-train | 9 |
| Partner Forward Deployed Engineer IV, GenAI, Google Cloud The Generative AI (GenAI) Forward Deployed Engineer (FDE) at Google Cloud is an embedded builder responsible for developing and deploying production-grade agentic AI solutions within partner and customer environments. This role bridges the gap between AI prototypes and reality by coding, debugging, and shipping bespoke solutions, addressing integration, data readiness, and state management challenges. The FDE also builds evaluation pipelines and observability frameworks, acts as a feedback loop to Google's product roadmap, and helps partners build their own agentic delivery capabilities, focusing on ROI and customer success. | AgentEval Gate | 9 |
| Staff Research Engineer, Applied AI, DeepMind Research Engineer to lead development and deployment of novel applications using Google's generative AI models. Focus on rapidly developing new features, collaborating with partner teams, and delivering solutions to maximize impact for Google and its customers. Role involves translating AI research into real-world products, demonstrating model capabilities, and scaling products from concept to production in fast-paced, early-stage environments. | AgentPost-train | 9 |
| Manager, Applied AI Engineering, DeepMind Manager for an Applied AI Engineering team at Google DeepMind, focused on leading the development and deployment of generative AI applications, translating research into products, and shipping software features for billions of users. | Ship | 9 |
| Research Scientist, Verified Code Generation, DeepMind Research Scientist role focused on developing AI systems for verified code generation using LLMs and formal methods, with a focus on programming language semantics and static analysis. | ShipData | 9 |
| Forward Deployed Engineer, GenAI, Google Cloud (English, Japanese) This role involves deploying and customizing Generative AI (GenAI) solutions for enterprise customers on Google Cloud. The engineer will build agentic workflows, integrate AI products with customer infrastructure, develop evaluation and observability pipelines, and provide feedback to product teams. The role requires strong software development skills, experience with AI systems, RAG, vector databases, and the ability to work with both technical and non-technical stakeholders in Japanese and English. | AgentEval Gate | 9 |
| Senior Software Engineer, Acceleration Platform Senior Software Engineer role focused on architecting and building AI-native agentic systems to automate developer tasks. The role involves leading the design of multi-agent networks, integrating LLM orchestration and RAG pipelines, establishing AI quality and safety standards, and developing evaluation frameworks and debugging tools. It emphasizes technical leadership, mentorship, and driving AI engineering excellence in complex, ambiguous initiatives. | AgentEval Gate | 9 |
| Senior Software Engineer, AI/ML, LLM Modeling This role focuses on training and deploying Large Language Models (LLMs) for search applications, involving reinforcement learning, multi-step reasoning, distillation, and optimizing model latency in production. The engineer will propose new modeling ideas, collect and evaluate training data, design evaluations, and collaborate on applying LLMs in real-world scenarios. | Post-trainServe | 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 |
| 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 |
| Research Software Engineer Research Software Engineer role focused on translating DeepMind's AI breakthroughs into AI/ML experiences for Google's Platforms and Devices (P&D) initiatives. The role involves architecting solutions, guiding product teams from concept to launch, and leading the end-to-end development of AI features, with a focus on shipping AI/ML products to billions of users. Requires experience with LLMs, NLP, and ML infrastructure, with a strong emphasis on building scalable ML infrastructure and leading technical architecture. | ShipServe | 9 |
| Forward Deployed Engineer, Generative AI, Google Cloud Consulting Forward Deployed Engineer for Generative AI on Google Cloud, focused on building and deploying bespoke agentic solutions within customer environments. This role bridges frontier AI products with production reality, addressing integration, data readiness, and state-management issues. Responsibilities include leading AI application development, architecting connective tissue between AI products and customer infrastructure, building evaluation pipelines and observability frameworks, identifying friction points for product feedback, and co-building with customer teams. | AgentEval Gate | 9 |
| Senior Product Manager, AI Garage Senior Product Manager for AI Garage at Google, focusing on defining and delivering AI-powered agentic products for HR processes. The role involves shaping AI-native product strategy, writing PRDs for systems with non-deterministic behavior (including fine-tuning and RAG), partnering with researchers on model requirements, pioneering multi-agent execution frameworks, and implementing LLM evaluation systems. Requires deep technical fluency in generative AI and experience launching technical products. | AgentPost-train | 9 |
| Research Software Engineer, Multimodal AI This role focuses on developing and enhancing AI agents, particularly in the multimodal domain (audio, vision), for XR devices. The engineer will work on LLMs, agents, and their integration into next-generation computing products, involving algorithm development, production-quality coding, evaluation planning, and shipping AI innovations. The role requires experience in software development, generative AI, ML frameworks, and multimodal learning. | AgentPost-train | 9 |
| Staff Software Developer, AI/ML, Safety and Security This role involves leading AI/ML projects focused on safety and security within Google Workspace. The primary responsibilities include building LLM-based safety and security auto-raters, developing classifiers for prompt injection attacks, and implementing live traffic observability solutions. The role also requires collaboration with Google DeepMind on research-based defense techniques and with various Workspace product teams to protect AI features. The ultimate goal is to ensure the safety and security of AI features across Google's productivity tools. | AgentServe | 9 |
| Forward Deployed Engineer V, Generative AI, Google Cloud This role involves deploying and building bespoke agentic AI solutions for enterprise customers on Google Cloud. The engineer will bridge the gap between frontier AI products and production reality, addressing integration, data readiness, and state-management challenges. Responsibilities include developing complex AI applications, architecting connective tissue between AI products and customer infrastructure, building evaluation pipelines and observability frameworks, identifying field patterns for product feedback, and co-building with pre-sales and product teams. The role requires strong software development experience, experience with production-grade AI solutions, and building data pipelines using vector databases and RAG. Experience with multi-agent systems and LLM-native metrics is preferred. | AgentServe | 9 |
| Staff Software Engineer, Quality, Google Cloud, Applied AI Staff Software Engineer focused on building and improving AI agents, specifically a meta-layer of agents that build, test, and refine other agents. The role involves developing multi-modal customer support agents with complex reasoning capabilities, embedding Gemini and Vertex AI into client-facing infrastructure, and establishing engineering benchmarks for automated optimization and AI quality assurance in production systems. | AgentEval Gate | 9 |
| Staff Software Engineer, AI Infrastructure, Google Cloud, Applied AI Staff Software Engineer focused on building and scaling high-performance, distributed infrastructure for agentic AI workflows in Google Cloud. The role involves transitioning experimental models into robust production services, ensuring low-latency and reliability for multi-agent systems, and iterating on customer needs for enterprise use cases. | AgentServe | 9 |
| Senior Software Engineer, Google Cloud, Applied AI Senior Software Engineer at Google Cloud focused on developing and deploying agentic AI solutions for enterprise use cases, leveraging Gemini Enterprise. The role involves algorithmic innovations for multi-agent systems, reinforcement learning, multimodal reasoning, and improving LLM reliability and tool use. | Agent | 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 Scientist, Google Research Research Scientist at Google Research focusing on fundamental research, new product innovation, and contributing to the wider research community by sharing and publishing findings. The role involves defining research strategy, developing prototypes, conducting experiments, and collaborating with internal and external partners. Requires a PhD and publication record, with experience in machine learning, data mining, and NLP. | Pretrain | 9 |
| Software Engineer, Foundational ML Research This role focuses on foundational ML research, prototyping algorithmic approaches, and designing/implementing solutions in specialized ML areas. It involves large-scale model training and applying research to post-training generative models. | PretrainPost-train | 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 |
| 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 |
| Senior Staff Technical Program Manager, AI Innovation and Research The Technical Program Manager will drive the strategy and execution of AI agent initiatives aimed at transforming the software development lifecycle, including democratizing app creation and building a virtual software engineering workforce. This role involves leading complex, cross-functional programs from 0-to-1, bridging foundational models with product applications, and ensuring safety and compliance. | Agent | 9 |
| Research Engineer, Pretraining, DeepMind Research Engineer at Google DeepMind focused on inference-optimized model design for Gemini pretraining. The role involves working across the LLM preparation stack (pretraining, fine-tuning, serving) and understanding XLA primitives and JAX on TPUs. Requires a Bachelor's degree and 5 years of experience in inference-optimized model design, with a preference for applied research experience in large transformer models and fine-tuning. | PretrainPost-train | 9 |
| Senior Research Engineer, On-Device Inference, Robotics, DeepMind Senior Research Engineer focused on optimizing Gemini Robotics models for low-latency on-device inference, driving alignment between model and hardware architectures, and influencing future model designs for resource-constrained environments. | ServeAgent | 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 Software Engineer Senior Software Engineer at Google DeepMind focused on building and improving agentic AI features using Gemini models. The role involves developing quantitative evaluations of agent performance, triaging production issues, and contributing to the technical vision and roadmap. Requires a PhD in a related field and experience in software development, algorithm design, systems architecture, Python for ML, and software testing. | AgentEval Gate | 9 |
| Senior Software Engineer Senior Software Engineer role focused on building and enhancing serving solutions for Gemini models, developing new infrastructure for advanced capabilities like large-scale streaming and audio logic, and ensuring the quality of models in production. The role involves collaborating with peers, driving technical vision, and requires experience in C++, algorithm design, debugging ML systems, and productionizing LLMs/multimodal models. | ServeAgent | 9 |
