Google

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.

Senior Staff Software Engineer role focused on mechanistic interpretability research for AI safety and alignment. The role involves designing and implementing cognitive architecture primitives for future agentic AI systems, guiding their development using agentic programming tools, and serving as a technical leader. Experience in speech/audio, reinforcement learning, ML infrastructure, or other ML fields is required, along with ML design and infrastructure experience.

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 Software Engineer to architect next-generation AI-native agentic systems for eliminating developer toil. Focus on defining paradigms for self-sustaining AI to resolve engineering issues, establishing AI engineering excellence and security-by-design, and scaling technical capabilities. Responsibilities include leading design of multi-agent networks, defining best practices blending distributed systems with LLM orchestration and RAG, establishing AI quality/safety strategy with automated evaluation, managing edge cases with advanced telemetry, and driving technical alignment and mentorship.

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.

Research Scientist role focused on utilizing LLMs for real-world tasks including rating scenarios, personalized evaluation, and simulating users to model preferences and behaviors. The role involves understanding academic literature, building and delivering functioning systems to Google products, and contributing to the wider research community through publications. The team's work is delivered in products like Search and Ads.

Research Scientist focused on improving the computational efficiency of large-scale generative AI models (LLMs, Diffusion Models, Generative Videos) through advanced algorithms, model compression, quantization, and optimization of training and inference pipelines. Collaborates with hardware and software teams to optimize kernels and inference engines.

Research Scientist focused on improving the computational efficiency of large-scale Generative AI Models (LLMs, Diffusion Models, Generative Videos) through algorithmic research, model compression, and inference acceleration. The role involves advancing algorithms for serving and inference, innovating training architectures, optimizing deployment pipelines, and collaborating with hardware/software teams. A PhD and publication record are required.

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 improving the computational efficiency of generative AI models (LLMs, Diffusion Models, Generative Videos) through foundational research in algorithmic efficiency, model compression, and inference acceleration. This role involves innovating algorithms, optimizing model architectures, improving the deployment pipeline (pretraining, tuning, RL), and collaborating with hardware/software teams to optimize inference engines and reduce latency/memory usage.

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.

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.

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.

Forward Deployed Engineer II, GenAI, Google Cloud - This role involves building and deploying bespoke agentic AI solutions for enterprise customers, managing integration complexities, data readiness, and state management. The engineer will act as a builder-consultant, transitioning prototypes to production, architecting connective tissue between AI products and customer infrastructure, and building evaluation and observability pipelines. The role also involves identifying field patterns to inform product roadmaps and mentoring talent.

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.

This role involves leading a team of developers to build and deploy agentic AI solutions within customer environments on Google Cloud. The focus is on bridging the gap between AI products and production realities, solving integration and data issues, and acting as a feedback loop for product development. The role requires coding, debugging, and shipping solutions, with responsibilities including building evaluation pipelines and observability frameworks.

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 Engineer focused on building safety mitigations for frontier AI models, defending against misuse in domains like CBRNE and Harmful Manipulation. Responsibilities include building classifiers, data pipelines, monitoring systems, and evaluating/securing agentic AI systems, with a strong emphasis on automated red-teaming and adversarial robustness research.

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.

Senior Forward Deployed Developer focused on applying Google's Generative AI, specifically building and deploying AI agents on the Customer Engagement Suite platform for enterprise clients. The role involves direct customer interaction, co-development, debugging, and optimizing AI solutions, acting as a bridge between product teams and customer needs to accelerate customer success and influence product strategy.

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.

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.

Senior Machine Learning Engineer focused on building and optimizing generative AI solutions for Google Cloud customers. This role involves working across the full stack of AI, from models and APIs to agent building blocks and specialized applications, with a strong emphasis on production environments and technical leadership.

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.

Senior Software Engineering Manager for Emergent AI Infrastructure, leading teams to build next-generation on-prem AI infrastructure for frontier models and AI solutions. Role involves technical leadership, team management, strategic guidance, and cross-functional collaboration across global sites to deliver high-impact AI infrastructure products.

Forward Deployed Engineer for Google Cloud, focused on building and deploying bespoke agentic AI solutions within customer environments. This role involves managing the full lifecycle from prototyping to production, including integration, data readiness, state management, and evaluation.