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, 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, 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 Scientist, Mechanistic Interpretability, Special Projects Research Scientist focused on mechanistic interpretability of large language models to ensure safety, alignment, and reliability. This role involves exploring emerging interpretability methods, developing open-source infrastructure, performing causal validation, and publishing findings. The scientist will also write code for experiments on distributed compute clusters. | Post-train | 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 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 |
| 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 |
| Senior Research Engineer This role focuses on applying AI research to real-world problems, involving prototyping, dataset curation, and deploying optimized ML systems. The Senior Research Engineer will architect and implement scalable software libraries and code in Python or C++, drive long-term research projects, and train/evaluate deep neural models and reinforcement learning algorithms. The role emphasizes influencing engineering best practices and communicating research developments. | 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 |
| Research Scientist, Google Research, GenAI, Experiences Research Scientist role focused on designing, implementing, and evaluating advanced ML models, with a focus on human preferences and behavior. The role involves architecting systems for model training and serving, performing statistical analyses, publishing research, and collaborating to integrate ML models into products. Requires a PhD and experience in ML, NLP, or computer vision, with a publication record. | Post-trainServe | 9 |
| Research Engineer, Agentic Security & Privacy Post-Training for Gemini, DeepMind Research Engineer focused on post-training Gemini models for security and privacy, specifically for agentic capabilities like coding and personal assistants. The role involves building training data and techniques to enhance security and privacy without sacrificing model capabilities, and collaborating on adversarial evaluation and guardrails. | Post-trainAgent | 9 |
| Senior Product Manager, Gemini Internationalization Modeling, DeepMind Product Manager for Gemini Modeling focused on internationalization, bridging research (pre-training, post-training, RL) with consumer needs. Owns roadmap, quality, evaluations, and data requirements for global AI efforts, establishing cross-lingual transfer playbooks and driving model readiness for launches. Works with research and engineering on global AI capabilities, including agentic coding and multimodality. | Post-trainAgent | 9 |
| Research Engineer, Gemmaverse Variants Research, DeepMind Research Engineer focused on developing and launching specialized Gemma variants, contributing to core LLM research tools and infrastructure, and enabling external users through documentation and collaboration. | Post-trainServe | 9 |
| Director, Research Commercialization (AI Blackbelts) Lead a global team of AI researchers and engineers to commercialize Google's frontier scientific AI models (e.g., AlphaFold, genomics LLMs) for life sciences and healthcare customers, focusing on co-engineering solutions for drug discovery and scientific modeling. | Post-trainPretrain | 9 |
| AI Cybersecurity Team Lead, DeepMind Lead an AI cybersecurity team focused on preventing malicious misuse of AI models and enhancing AI's cyber defense capabilities. This involves overseeing defense strategies across the technical stack, translating research into production deployments, and understanding the AI research to product integration pipeline. The role also involves publishing influential work and contributing to flagship products like Gemini. | Post-trainServe | 9 |
| 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 |
| Staff Software Engineer, Applied Research, Foundation User Models Staff Software Engineer, Applied Research, Foundation User Models at Google. This role focuses on defining and executing the applied research roadmap for Large User Models, translating business goals into technical formulations, optimizing model performance with adaptation techniques, driving architectural improvements by influencing pre-training teams, and productionizing fine-tuning pipelines for recommendation engines. The role requires experience with Transformer-based models and ML design, with a focus on balancing quality output with strict inference latency requirements. | Post-trainServe | 9 |
| Staff Software Engineer, User AI Flywheel, Search Intelligence Staff Software Engineer focused on the User AI Flywheel for Google Search, aiming to enhance LLM performance, quality, and capabilities through user signals and advanced modeling techniques. The role involves innovating on LLM improvements, partnering with research teams, and integrating LLM technologies into products. Responsibilities include advocating for modeling/tuning/optimization, designing user signal-driven improvements, collaborating with research, and demonstrating expertise in system design, ML modeling, and coding for LLMs. The role requires experience in software development, ML design, ML infrastructure optimization, and GenAI techniques, with preferred experience in RLHF, fine-tuning, and ML systems production. | 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 |
| Visiting Faculty Researcher, AI Personalization Visiting Faculty Researcher at Google focusing on AI Personalization. The role involves proposing novel ideas for models that learn continuously from user interactions, adapt with minimal data, and deploy efficiently on personal devices. This research position emphasizes contributing to the academic community through publications and collaborating on research proposals, while also influencing product development with potential applications in generative AI, prompt engineering, and personalization. | Post-trainAgent | 9 |
| Staff Research Engineer, Gemini Audio, DeepMind Staff Research Engineer focused on Gemini Audio at DeepMind, developing multimodal models (audio/audio-visual) and driving end-to-end development from pretraining to production systems, utilizing RL frameworks for training infrastructure and model training. | Post-trainServe | 9 |
| Audio Algorithm Architect, Applied Research Applied Research role focused on foundational audio algorithms for Pixel and Buds, specifically Superhuman Hearing and Open Ear ANC. The role involves exploratory, non-timeline-based research in a high-velocity, startup-style team, aiming for massive user differentiation and defining agentic audio experiences. | Post-train | 9 |
| Staff Research Scientist, Google Ads GenAI Research Scientist role focused on adapting Gemini models for Google Ads using prompt engineering, fine-tuning, and reinforcement learning. The role involves developing novel ML modeling techniques, working with LLMs for targeting and retrieval, collaborating with DeepMind and Search teams, and publishing research findings. | 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 Software Engineer, Generative AI, LearnX Senior Software Engineer focused on Generative AI for learning products within Google Search and Lens. Responsibilities include developing AI features, fine-tuning models, optimizing prompts, evaluating performance, and launching AI-driven features. Requires experience in AI/ML engineering, software development, and technical leadership. | Post-trainAgent | 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 III, 3D Modelling, XR Google is seeking a Machine Learning Engineer with a focus on 3D geometry to work on the convergence of AI and XR. The role involves managing the end-to-end training process for ML models, optimizing them for various environments, and ensuring data quality and robustness. The engineer will adapt research in monocular depth modeling for real-world scenarios, bridging the gap between research and product requirements. | Post-trainServe | 8 |
| Software Engineer Software Engineer at Google DeepMind focused on applying research to high-impact GenAI problems, curating datasets, and building ML pipelines for generative media, multimodal understanding, and reinforcement learning. Responsibilities include developing robust product code, performing comprehensive testing, collaborating with peers, triaging and resolving complex system issues, and managing the full deployment lifecycle. | Post-trainData | 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. The role involves developing and testing robust product code, collaborating with peers, triaging issues, creating documentation, and managing the full deployment lifecycle. | 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 |
| Senior Software Engineer, AI/ML Senior Software Engineer, AI/ML role focused on developing and launching AI-driven learning features for Google Search and Lens. Responsibilities include data preparation, fine-tuning, prompt optimization, performance evaluation, and cross-functional collaboration. | Post-trainAgent | 8 |
| Senior Software Engineer, AI/ML, Google Meet Senior Software Engineer focused on AI/ML for video quality optimization and understanding in Google Meet. Responsibilities include developing ML models for video enhancement, segmentation, and understanding, collaborating on best practices, and driving AI/ML development in the video domain to create tangible features for users. | Post-train | 8 |
| Senior Research Software Engineer, Google Research Research Software Engineer at Google Research focused on developing and deploying vision models for Auto HD Mapping to improve autonomous driving capabilities. The role involves the full ML lifecycle from literature review and data collection to model training, tuning, evaluation, and deployment, leveraging existing Google models and technologies. | Post-train | 8 |
| Software Engineer III, Machine Learning, Search Intelligence Software Engineer III, Machine Learning, Search Intelligence at Google, focused on developing and deploying core ranking and machine learning models for Google Search. The role involves building data pipelines, contributing to model distillation, and maintaining training infrastructure to improve performance for challenging queries, particularly for long-tail query scenarios. The position requires experience in software development, ML infrastructure, and potentially speech/audio, reinforcement learning, or other ML specializations. | Post-trainServe | 8 |
| Senior Software Engineer, Gmail Abuse and Safety Protections Senior Software Engineer role focused on protecting Gmail users from abuse, particularly leveraging GenAI and ML techniques. The role involves assessing threats from new technologies like GenAI, designing safeguards, driving improvements through ML algorithms and systems, and building production-ready ML systems. It requires experience with ML infrastructure, GenAI techniques, and data analysis, with a focus on applied machine learning in user-facing products and safety/abuse fighting. | Post-trainServe | 8 |
| Staff Engineering Analyst Manager, Veo and Robotics This role leads a team of engineering analysts focused on AI safety for foundational models like Gemini, Veo, and Robotics. Responsibilities include developing introspection heads, post-training models for safety alignment, building LLM-based safeguards, and generating insights from model logs. The role emphasizes collaboration across Google DeepMind and Trust & Safety, strategic direction for model launches, and rigorous auditing of model safety. | Post-trainAgent | 8 |
| Senior Staff Engineering Analyst Manager, Gemini, NanoBanana, Veo Senior Staff Engineering Analyst Manager for Gemini, NanoBanana, Veo, focusing on Introspection and post-training model mitigations. The role involves leading and scaling a team, pioneering safety mitigation architectures using technologies like supervised fine tuning and direct preference optimization, driving cross-functional alignment, directing foundational model launch strategies, and applying data science to audit model safety. Requires 8 years of experience in data science/ML and 5 years in technical leadership/people management. | Post-train | 8 |
| Software Engineer III, Google Home Video Intelligence Software Engineer III at Google Home Video Intelligence, focusing on building and deploying real-time camera video understanding for smart home devices. Responsibilities include writing product code, participating in design reviews, reviewing code, contributing to documentation, and researching, training/fine-tuning, and applying ML/LLM models for video understanding. | Post-trainServe | 8 |
| Senior Software Engineer, AI/ML Senior Software Engineer, AI/ML at Google, focusing on developing and launching AI-driven learning features for Search Web and Lens. Responsibilities include managing AI feature design, analyzing model performance, leading cross-functional collaboration, and ensuring AI/ML best practices. Requires 5 years of software development, 3 years in AI/ML engineering, and 1 year in technical leadership. | Post-trainData | 8 |
| Senior Applied ML Engineer, Graph Neural Network, ML Frontiers Senior Applied ML Engineer focused on Graph Neural Networks within the ML Frontiers team, collaborating on LLM agents and decision forests. The role involves feature development, research exploration, and client collaboration, bridging pioneering models with enterprise solutions. | Post-train | 8 |
| Software Engineer III, AI/ML, YouTube Shopping Google is seeking a Software Engineer III, AI/ML for their YouTube Shopping team in Zurich. The role involves designing, implementing, and deploying ML models for tasks like Product Detection and Video Classification, building training data pipelines, and ensuring model performance through evaluation frameworks. The engineer will also contribute to the back-end infrastructure for efficient model serving at scale and implement solutions in specialized ML areas. | Post-trainServe | 8 |
| Senior Software Engineer, Machine Learning, Vertex AI Senior Software Engineer on the Vertex Generative AI Media team, focusing on transforming generative models into high-performance engines for enterprise customers. The role involves managing post-training issues, including Multimodal Supervised Fine-Tuning (SFT) and Latent Distillation, to ensure brand-aligned, production-grade media generation. The engineer will build custom-tailored Generative Media by fusing Google's video and image foundations with proprietary enterprise data. | Post-trainServe | 8 |
| Senior Software Engineer, AI/ML, Google Meet Senior Software Engineer focused on AI/ML for video quality optimization and understanding in Google Meet. Responsibilities include developing ML models for video enhancement, segmentation, and understanding, collaborating on best practices, and driving AI/ML development in the video domain to create tangible features for users. | Post-train | 8 |
