Research Scientist at Google DeepMind Robotics focused on building foundation models, specifically vision-language-action (VLA) models, for physical agents to enable robots to perceive, plan, think, use tools, and act. The role involves advancing general-purpose robotics through research in areas like agentic reasoning, real-world understanding, and human-robot interaction, with the goal of deploying these innovations at scale.

Research Scientist role focused on applying machine learning to discover novel Quantum Error Correction (QEC) codes for fault-tolerant quantum computing, specifically for superconducting qubits and high-connectivity platforms. The role involves developing large-scale automated discovery pipelines, optimizing codes for quantum processors, and contributing to the research community through publications and collaborations.

Google DeepMind is seeking a Frontier AI Research Scientist to push the boundaries of AI development, focusing on advancing AI for complex global challenges and product innovation. The role involves authoring research papers, defining research frameworks, identifying new research areas, and conducting experiments to evaluate research impact. The position requires a PhD and at least one scientific publication submission.

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.

Research Scientist role focused on designing, developing, and deploying agentic AI solutions for enterprise use cases within Google Cloud's Applied AI division, specifically powering business growth with Gemini Enterprise. The role involves taking ownership of AI quality for production systems, implementing and optimizing AI techniques, and driving progress through experimentation. Collaboration with model builders and contribution to the research community through publications are also key aspects.

The Actor Safety Foundational Modeling (ASFM) team is looking for a Senior Software Engineer to build core ML models and infrastructure for detecting and preventing abusive behavior in Google Ads. This role involves developing AI/ML models, leveraging LLMs and agent infrastructures, building and deploying AI agents for investigation and threat hunting, and creating scalable infrastructure for safety operations. The position emphasizes innovation and rapid deployment of generative AI solutions to stay ahead of adversarial tactics.

Senior Staff Software Engineer role focused on designing, developing, and deploying large-scale AI solutions, with a specific emphasis on language models and agentic systems. The role involves technical leadership, ML infrastructure optimization, and applying the latest AI technologies to create impactful products. Requires extensive experience in software development, ML design, and industry ML infrastructure.

Research Scientist at Google DeepMind focused on advancing Gemini's capabilities in autonomous knowledge acquisition, reasoning, and retrieval. The role involves designing modeling innovations, improving retrieval architectures, building self-improving models, and collaborating with product teams to scale research into production. Emphasis on next-generation retrieval, multimodal representations, and autonomous reflection/self-improvement.

Staff Software Engineer role focused on leading the technical strategy, architecture, and delivery of a new agentic video creation application for YouTube Ads. The role involves developing multi-modal agentic systems using Generative AI to produce high-fidelity video creatives at scale, adapting frontier AI capabilities to the Ads domain, and designing scalable APIs and microservices. This position bridges frontier AI with business impact and requires experience in leading applied AI/ML products and shipping AI applications.

Staff Software Engineer at Google DeepMind on the Gemini App Personalization team, focused on building a next-generation AI assistant that deeply personalizes products for users. The role involves designing and building scalable features for capturing, organizing, and surfacing personal context, performing data analysis, developing evaluation techniques for contextual recall, owning model output quality, and contributing to a data flywheel. The position requires significant software development experience, particularly with big data, ML, LLMs, and data analysis, with a focus on creating a seamless cognitive extension for users.

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.

Research Scientist focused on security and privacy for AI models and agentic products, specifically Gemini. The role involves designing and evaluating novel defense mechanisms against adversarial attacks and prompt injections, translating research into practical solutions for training and inference pipelines, and collaborating with core modeling and engineering teams. The position requires a PhD and experience in ML research, benchmarking, and security, with a focus on next-generation security techniques for autonomous AI systems.

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.

Staff Datacloud Blackbelt Engineer role focused on building and deploying sophisticated Data and AI agents and solutions for enterprise customers, leveraging Google's AI technologies. The role involves architecting, optimizing inference latency, and transforming bespoke solutions into reusable assets, acting as a technical lead and mentor.

Forward Deployed Engineer (FDE) role focused on building and deploying generative AI agentic solutions for Google Cloud customers in the telecommunications sector. This role involves coding, debugging, and integrating AI products into customer environments, managing integration complexities, and providing feedback to product teams. It requires a blend of engineering, customer engagement, and problem-solving skills to deliver bespoke AI applications and reusable assets.

Staff Software Engineer focused on leveraging AI/ML, including LLMs and Agentic AI, to enhance search ads experiences, optimize ad performance, and build AI-first systems. The role involves designing, developing, and deploying AI/ML models and evaluation methods for data quality assessment within the Google Ads product.

Forward Deployed Engineer IV, Applied AI, Google Cloud. This role focuses on transforming conversational AI prototypes into production-ready solutions for customers, owning the end-to-end engineering lifecycle. Responsibilities include architecting and coding conversational flows, building evaluation pipelines and observability frameworks for agentic workloads, and ensuring best practices for customer projects. Requires experience with AI systems on cloud platforms, deploying conversational agents, and full-stack application development interacting with enterprise IT.

Research Engineer focused on inference-optimized model design for Gemini pretraining, working across the LLM preparation stack (pretraining, fine tuning, serving) and understanding JAX/TPU execution. Requires 5 years of experience in inference-optimized model design and experience with product teams.

Google is seeking a Forward Deployed Engineer for the DevAI team to accelerate its transformation into an AI-native company. This role involves partnering with Product Areas to build and elevate AI capabilities, focusing on the technical foundation of Google's flagship products. The engineer will lead the design and implementation of autonomous, agentic workflows, deliver production-grade agent components, and re-engineer isolated solutions into scalable capabilities.

Research Scientist role focused on developing new algorithms in AI for mathematics and theoretical research, with a focus on privacy and machine learning, and translating these insights into Google products. The role involves publishing research in top conferences.

Senior Research Engineer focused on optimizing Gemini Robotics models for low-latency on-device inference, driving alignment between model architectures and edge device constraints, and influencing research and engineering teams for robust solutions. Requires deep knowledge of inference techniques across GPU, TPU, and CPU architectures.

Technical Program Manager at Google DeepMind focused on driving the execution of agentic capabilities from research to production, specifically for Gemini and other Google products. This role involves managing the lifecycle of agentic innovations, building pathways between research and product teams, and understanding the AI model development lifecycle.

Research Scientist focused on visual data and generative models, specifically for creating high-quality synthetic training data for foundation models. This involves designing data acquisition strategies, optimizing hardware, implementing fine-tuning methods, developing automated labeling pipelines, and creating evaluation datasets for visual quality issues.

Research Scientist role focused on developing Vision Language Action (VLA) models and agentic systems for physical robots, enabling them to perceive, plan, think, use tools, and act in real-world environments. The role involves training embodied reasoning VLMs, working with simulators and real robots, and advancing areas like general-purpose robotics, human-robot interaction, and continual learning.

Research Engineer at Google DeepMind focused on architecting, scaling, and landing latent thinking in Large Language Models (LLMs) and reasoning. The role involves developing novel algorithms, formulating research hypotheses, designing and implementing ML experiments, and partnering with teams to integrate scientific breakthroughs into frontier models. Experience in LLM training (pre-training or post-training) and publishing research is preferred.

Research Engineer focused on building and deploying advanced safety mitigations for frontier AI models, specifically defending against misuse in domains like Cybersecurity and CBRNE. The role involves creating novel evaluations, red-teaming, implementing robust defenses, and monitoring risks, with a strong emphasis on agentic AI systems and adversarial robustness.

Product Manager for Gemini's agentic capabilities, focusing on defining excellence, scaling evaluation frameworks, and driving research. The role involves bridging model research and ecosystem needs through data-driven methods, synthetic data generation, and loss analysis, with a specific emphasis on tool use and agentic evaluations.

This role focuses on defining and driving the power architecture roadmap for Google's next-generation TPUs, which are AI/ML hardware accelerators. The architect will bridge the gap between high-level concepts and silicon execution, optimizing for performance-per-watt for ML workloads and ensuring successful implementation of power management features. This involves collaboration with various teams, including SOC implementation, hardware/software validation, and data center operations, to align silicon capabilities with system-level power constraints. The role requires deep expertise in computer chip design, performance analysis, and power analysis, with a strong emphasis on machine learning accelerator architecture and workload characterization for power optimization.

Staff Software Engineer on the Gemini App Personalization team, building next-generation personal AI assistants using Gemini models. Responsibilities include developing personalization capabilities, model post-training, evaluation, data handling, serving, and production deployment. Also involves creating systems for agent testing, developing test problems, visualizing results, building leaderboards, and testing algorithms on robots.

Software Engineer role at Google DeepMind focused on building and testing AI agents. Responsibilities include developing agent testing systems, creating test problems in simulators, visualizing results, building leaderboards, and testing algorithms on robots. The role involves working on both frontend and backend infrastructure for AI tools, improving LLMs, and integrating AI into Google products. Requires strong software engineering skills and experience with Generative AI Agents.

Forward Deployed Engineer for Generative AI in the Media & Entertainment sector on Google Cloud. This role involves building, debugging, and shipping bespoke agentic solutions directly within customer environments, bridging the gap between frontier AI products and production reality. Responsibilities include developing complex AI applications, architecting integrations, building evaluation pipelines, and providing feedback to product teams. Requires experience in production-grade AI solutions, cloud platforms, data pipelines with vector databases and RAG, and leading technical discovery.

Forward Deployed Engineer for Google Cloud's Generative AI Go-To-Market organization, focusing on building and deploying end-to-end GenAI solutions for customers. This role involves rapid prototyping, integrating AI/ML with the broader cloud stack, and translating customer needs into scalable assets.

Staff Software Engineer role focused on developing and optimizing on-device and hybrid multimodal AI models (LLMs, agents, vision, audio) for XR devices. Responsibilities include leading development, creating evaluation plans, implementing innovations in agent architectures and multimodality, rapid prototyping, and collaborating with research and product teams. Requires strong software development experience with C++, Python, and Generative AI, along with ML/AI experience.

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.

Research Engineer focused on developing monitoring and control systems for potentially misaligned AI agents to mitigate risks of extreme harms. This involves designing, building, and testing monitors, implementing response policies, and conducting adversarial testing. The role aims to prepare for the internal use of potentially misaligned AI systems by building defense-in-depth against AI that might persistently pursue unintended goals.

Staff Software Developer on the GAWSS team responsible for building and implementing AI/ML-based safety and security mitigations for Google Workspace products. This includes developing LLM-based auto-raters, classifiers for prompt injection attacks, and live traffic observability solutions. The role involves collaboration with Google DeepMind on research and with various product teams to protect AI features across Workspace applications.

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.

Senior Staff Research Engineer at Google DeepMind focused on Agent Evals and Quality for GenAI model improvement and product development. The role involves developing, evaluating, and optimizing LLM-based agents for complex, multi-step tasks. Responsibilities include constructing quantitative benchmarks and automated evaluation frameworks (e.g., LLM-as-a-judge) to measure agent capabilities in reasoning, planning, and tool use, as well as creating and optimizing data mixes from user feedback for training and fine-tuning agents. The role also requires analyzing agent behavior to identify failure modes and performance bottlenecks.

Staff AI Research Engineer focused on architecting the strategy and roadmap for foundation recommender model pre-training. This role involves owning the research agenda, defining and prioritizing experiments for model quality under compute constraints, and partnering with data, ML infrastructure, and engagement teams to shape roadmaps, define training framework requirements, and establish evaluation benchmarks.

Staff Software Engineer at Google Cloud AI Research focused on designing, developing, and deploying GenAI solutions. This role involves leading the design of GenAI solutions, optimizing ML infrastructure, and guiding the development of data preparation and model optimization strategies. Requires significant experience in software development, ML infrastructure optimization, and state-of-the-art GenAI techniques.

Senior Staff Software Engineer focused on building and delivering ML frameworks for training large language models (LLMs) and stable diffusion models for Google Cloud customers. The role involves designing and implementing AI frameworks software for various ML workloads, identifying and resolving software and performance issues, and collaborating with cross-functional teams. Requires extensive experience in software development, ML design, ML infrastructure, and leading technical projects, with a focus on training ML models at scale.

Staff Software Engineer role focused on architecting and implementing Agentic Reinforcement Learning systems. This involves developing novel RL recipes, reward modeling, and synthetic data for reasoning, planning, and tool use in large-scale AI products. The role bridges frontier research with production, focusing on the "GenAI Engineering Gap" to create self-improving agentic systems.

Staff Software Developer role focused on developing and deploying agentic AI solutions for enterprise use cases. The role involves inventing, designing, and deploying systems with a focus on algorithmic innovations for sophisticated agentic AI, including multi-agent systems, reinforcement learning, multimodal reasoning, and enhancing LLM reliability and tool use. The position also involves managing and iterating on new platform capabilities and driving technical strategy for a conversational AI platform.

Research Scientist role focused on designing, developing, and deploying agentic AI solutions for enterprise use cases within Google Cloud's Applied AI team. The role involves applying AI/ML to conversational problems, working with Gemini Enterprise products, and contributing to the wider research community through publications. Responsibilities include owning AI quality for production systems, implementing and optimizing AI techniques, and driving progress through experimentation.

Staff Software Engineer focused on optimizing AI/ML training and serving workloads on TPUs. This role involves identifying performance bottlenecks, driving optimizations through custom kernels, compiler/runtime improvements, and collaborating with partner teams to achieve state-of-the-art performance for foundation model builders and hyperscalers. The position also involves algorithmic innovation and co-designing TPU-friendly models.

Senior Software Engineering Manager for Google Cloud AI, focusing on GenAI. This role involves leading teams of engineers, setting technical vision and roadmap, overseeing system designs, and driving the strategy for large-scale ML infrastructure optimization and state-of-the-art GenAI solutions. The team addresses AI challenges for various industries, aiming to push AI's state-of-the-art and collaborate with product teams.

Research Scientist role focused on fundamental AI research, developing new products, and contributing to the research community. The role involves defining research strategies, designing experiments, and publishing findings, with a focus on machine learning and deep learning.

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.