Engineering Manager for Woodshed, a core AI/ML infrastructure team at Google, focusing on distributed systems for machine learning, dataset lakehouse management (Canon), and supporting multimodal model training for various Google product areas like Gemini and GenMedia. The role involves managing a team, contributing to product strategy, and building next-generation AI/ML systems.

Staff SWE role focused on architecting and owning the accuracy and fidelity of a critical co-design simulation platform for next-generation ML accelerators. The role involves establishing correlation infrastructure between simulated and physical hardware, evolving the simulation layer for complex workloads like LLMs, and identifying system-level bottlenecks at the pre-silicon stage to provide performance estimates for future ML systems.

Product leader for Google Labs focused on incubating 0-1 AI products, identifying whitespace opportunities, and navigating ambiguity to achieve product-market fit. Requires experience building AI-native consumer or creative products from conception to launch.

Staff Software Engineer at Google Cloud, focusing on AI/ML for Identity and Access Management infrastructure. The role involves architecting and implementing agentic authorization solutions, leading the integration of AI/ML into IAM, and driving the technical vision for scalable infrastructure systems. This includes building a platform for customers to deploy multi-agent ecosystems and connect LLMs securely within GCP. The position also involves technical leadership, mentoring engineers, and ensuring system operational health.

Senior Software Developer role focused on Computer Vision and XR at Google. The role involves developing and deploying geometric sensing capabilities for XR products, enabling features like 3D reconstruction and scene understanding. It requires experience with ML infrastructure, computer vision systems, and Augmented Reality. The position contributes to the convergence of AI and XR to create augmented human intelligence experiences.

Quantitative UX Researcher focused on user behavior and product quality/trust within Google Search, leveraging empirical methods and collaborating with engineering and product teams. The role involves analyzing user data, influencing stakeholders, and driving product improvements, with a requirement for experience in shipping ML, NLP, or LLM-powered products.

Senior Software Engineering Manager for Google's XR Platform, focusing on AI-powered interfaces and agentic systems. This role involves technical leadership, team management, and defining roadmaps for next-generation XR experiences that converge AI and XR technologies.

This role is for a Senior Data Cloud Blackbelt Manager at Google, focused on incubating and accelerating the adoption of Google's data cloud and AI capabilities for enterprise customers. The manager will lead a team in building and deploying sophisticated AI agents, acting as a technical counterpart to customer executives and influencing product roadmaps.

Director of Product Management for Safety & Privacy for the Gemini App, focusing on building trustworthy and secure generative AI products. The role involves leading a team to develop safeguards against AI risks, design privacy controls, and ensure data governance, while meeting global regulatory standards. Requires technical understanding, regulatory awareness, and leadership.

Software Engineer III role within Google Ads focusing on implementing ML solutions, utilizing ML infrastructure, and contributing to model optimization and data processing. Requires experience in programming (Python/C++) and ML infrastructure, with a specialization in areas like speech/audio, reinforcement learning, or other ML fields.

Staff Software Engineer for Gemini Live, a multi-modal AI assistant focused on user interaction, productivity, and learning experiences. The role involves defining and driving front-end architecture, engineering multi-modal experiences, developing non-verbal communication systems for low-latency responses, and partnering with GenAI/Model teams to integrate advanced capabilities and establish quality metrics.

Software Engineer III role focused on building and maintaining evaluation pipelines, safety classifiers, and automated testing systems for AI skills within the Chrome product. This involves designing and implementing metrics, visualization tools, and auto-raters to ensure the quality, safety, and performance of AI workflows, with a focus on integrating with various AI models and browser surfaces.

Staff Software Engineer at Google Cloud focused on building an organization-wide fleet health platform for databases. This platform leverages LLMs and AI to provide actionable insights, unified management, and a conversational agent for customers to pinpoint and resolve issues in their database fleet. The role involves designing and building centralized fleet management systems, partnering with product and engineering teams, and improving the operational health of these systems.

Senior Software Engineer role focused on building and shipping Gemini applications on Android, translating AI capabilities into user-friendly mobile experiences. This involves architecting scalable mobile systems, developing server-side logic, and owning CoreUI libraries for new model capabilities.

Senior Software Engineer role focused on building and operating Generative AI products for the public sector, involving data synthesis, retrieval applications, ML inference optimization, and ML infrastructure management.

Engineering Manager for AI/ML networking safety solutions, focusing on leading a team to develop and deploy these solutions into production. The role involves managing project priorities, team development, and cross-functional collaboration within Google's AI and Infrastructure team.

This role focuses on ensuring the safe launch of Generative AI models, acting as a key advisor and strategist for cross-functional teams. It involves anticipating risks, designing testing strategies, analyzing results, and driving mitigation and post-launch monitoring, with a specific emphasis on Text Models, Model Personalization, Model Governance, and Health/Mental Health.

Software Engineering Manager II for the Deep Research team within the Agentic Validation organization, focusing on building agentic AI solutions to improve coding agents. The role involves technical leadership, people management, and driving projects related to codebase intent extraction, exploratory testing, and agentic validation.

Software Engineer role focused on applying AI/ML to optimize the fault tolerance and reliability of Google's global data center fleet, including ML TPUs. The role involves designing and implementing ML models for fault prediction and mitigation, analyzing large-scale telemetry data, and building scalable automated systems. It requires experience in ML infrastructure, model deployment, and data processing, with a focus on improving the reliability of AI/ML systems and traditional compute infrastructure.

Senior Software Engineer role focused on Generative AI within Google Ads, specifically on Ads Safety. The role involves developing and testing product/system code, participating in design reviews, and reviewing code. Requires experience with ML infrastructure, state-of-the-art GenAI techniques (LLMs, Multi-Modal, Large Vision Models), and GenAI-related concepts. Preferred qualifications include experience with Generative AI Agents and applied ML.

Image Processing Engineer role focused on optimizing image quality by fine-tuning algorithms and building ML-powered tools for tuning, testing, and calibration workflows. Requires experience in image quality, computer vision, Python, and C++.

Technical Lead for AI/ML Storage at Google, focusing on managing and optimizing storage solutions for AI/ML workloads. This role involves leading product design, developing AI/ML client libraries, and driving storage innovation across Google Cloud Platform services. Requires extensive software development experience, including building ML solutions and infrastructure, with a focus on performance engineering and the evolving AI/ML landscape.

This role focuses on optimizing the performance of machine learning software and hardware stacks, particularly for TPUs, by providing performance debugging and analysis for ML workloads and custom kernels. The engineer will contribute to the end-to-end stack and analysis tools to support new ML paradigms and partner with teams to deliver chip profiling requirements.

Senior Software Engineer role focused on the convergence of AI and XR, developing full-stack imaging and camera solutions for XR devices. The role involves optimizing software layers for quality, latency, and power efficiency, evaluating and developing technologies for next-generation products, and collaborating across various Google teams and external partners. Experience in imaging, computer vision, and ML perception is required, with a focus on shipping AI-powered XR products.

Staff UX Front-End Engineer for YouTube, focused on building high-fidelity prototypes and experimental frameworks for GenAI-driven creation tools. The role involves establishing a prototyping program with shared sandboxes and reusable toolsets to enable designers to create functional prototypes reflecting AI-driven media generation. Responsibilities include leading prototyping for AI video features, developing a creation design system, and driving the design-to-code evolution.

Product Manager for YouTube Ads User Quality, focusing on ML algorithms, auction design, and relevance models to improve ranking systems and user experience. This role involves defining metrics, designing A/B tests, and partnering with engineering and data science teams to develop and deploy next-generation ranking models.

Senior Software Engineer role focused on AI/ML within Google Search, involving the design and implementation of solutions in specialized ML areas, leveraging ML infrastructure, and contributing to product/system development. The role requires experience with ML infrastructure, model deployment, evaluation, optimization, and specific ML fields like Recommendation Systems or reinforcement learning.

Staff Software Engineer for YouTube Shopping Recommendations, focusing on applied machine learning and recommendation systems to enhance the shopping experience within YouTube. The role involves technical leadership, driving viewer growth through ML algorithms, and collaborating across teams to build and deploy these systems at scale.

Staff Software Engineer role focused on building and enhancing large-scale AI/ML systems for YouTube Ads, specifically for user interest modeling and ad recommendation. The role involves technical leadership, designing and implementing ML solutions, optimizing ML infrastructure, and guiding model optimization and data processing.

Product Strategy and Operations Principal for Google Cloud AI, focusing on evolving legacy systems to Agentic ecosystems. This role involves strategic analysis, roadmap development, and translating AI infrastructure needs into business strategies and Go-To-Market plans, with a focus on designing agent systems.

Software Engineer role focused on 3D computer vision, specifically camera calibration workflows and algorithms, from conception to factory deployment. Responsibilities include creating system requirements, designing experiments, authoring monitoring dashboards, and managing calibration station bring-up at manufacturing sites. Requires experience with ML infrastructure and computer vision.

This role focuses on shaping generative AI experiences within Google Search by leading model behavior design, content strategies, and training methods. The Staff UX Content Designer will develop frameworks, rubrics, and evaluation methods to ensure high-quality, trustworthy responses, working closely with researchers, PMs, and engineers. The role emphasizes influencing response quality, building user confidence, and defining standards for a reliable search experience.

This role focuses on developing and deploying AI/ML models within Electronic Design Automation (EDA) CAD tool flows for AI/ML hardware acceleration, specifically Google's TPUs. The engineer will architect, develop, and implement software systems to automate and optimize chip design processes, focusing on improving Power, Performance, and Area (PPA) and Turn Around Time (TAT). The role involves a blend of hardware design, software engineering, and AI/ML application within the silicon development lifecycle.

AI Engineer role focused on delivering and evolving a Generative AI curriculum for global participants, applying AI solutions to business challenges, and leading customer educational journeys. The role involves designing AI/ML curriculum, staying updated on ML developments, and serving as an ML subject matter expert for Google Cloud Consulting.

This role focuses on the RTL design and verification of PCIe subsystems for Google's next-generation Tensor Processing Units (TPUs), which are custom accelerators for AI/ML workloads. The engineer will architect and implement SoC-level RTL, focusing on foundational infrastructure like clocking, reset, and error handling, and collaborate with hardware and software teams throughout the product lifecycle. The position involves leading PCIe microarchitecture, RTL development, integration, and post-silicon bring-up, requiring expertise in ASIC design, PCIe protocols, and verification methodologies.

This role focuses on shaping product experiences through content design and UX writing, with a significant emphasis on conversational AI and driving the behavior of AI models. The responsibilities include establishing model training practices, writing content for AI, and evaluating response quality. The role also involves developing AI-driven prototypes and working with multi-modal interfaces, indicating a strong connection to building and refining AI systems.

Software Engineer III role at Google Play focused on implementing ML solutions, utilizing ML infrastructure, and contributing to model optimization and data processing. The role involves writing product/system development code, collaborating with peers, contributing to documentation, triaging issues, and debugging. Requires experience in Python/C++, and ML infrastructure or a specialization in an ML field like speech/audio or reinforcement learning.

Staff Software Engineer to lead the technical strategy for a Generative AI pillar focused on building an extensible agent platform for automating compliance execution within Google Cloud Platform services. Responsibilities include static code analysis, auto-generating compliance code, and providing chat assistance for technical questions.

Senior Staff Software Engineer role focused on defining the roadmap and architecture for Agentic Applications within Google Cloud. The role involves developing an intelligent query layer, driving cross-organizational collaboration for agent ingestion and serving, and owning complex roadmaps related to exabyte-scale storage solutions for these applications.

Software Engineer role focused on transforming a web application (NotebookLM) to support interconnected AI agents and long-running, goal-seeking tasks, balancing user simplicity with agentic workflow power for mass consumer markets. The role involves end-to-end feature prototyping and building, linking back-end capabilities to user journeys, and driving engineering-product alignment in an evolving AI space.

Senior Technical Solutions Consultant role focused on architecting and implementing a Digital Twin ecosystem for Google's consumer hardware product design and manufacturing. The role involves full-stack GCP cloud-native development, integration of Vertex AI/Gemini Enterprise, and pioneering autonomous agents for insights and automations. Responsibilities include engineering microservices, deploying and monitoring AI agents, and leading code reviews for both full-stack code and agentic orchestration.

Staff Software Engineer focused on building and launching tools and solutions for GenAI data generation and evaluations. The role involves developing a self-service data generation platform, performing LLM/GenAI model evaluations, and fine-tuning models using techniques like RLHF. The engineer will work cross-functionally to deliver high-quality data sets and evaluation infrastructure for various GenAI use cases.

Senior Software Engineering Manager for Mobile Maps Innovation at Google. This role involves leading strategy and execution for new ways users search and interact with the physical world, focusing on leveraging location history and on-device components to provide intelligent, predictive context. The manager will oversee feature development, drive user-facing product initiatives (e.g., monetization), manage cross-functional projects, and grow/mentor a team. A key aspect is driving GenAI adoption and managing the deployment of models like Gemini Nano on hardware for validation.

Staff Data Scientist role focused on personalization and quality for Google Discover, involving the development and improvement of retrieval and ranking ML systems. The role requires leveraging AI and LLM techniques to enhance user experience and product growth, with responsibilities including analysis, research, and technical leadership.

The role focuses on applying AI and agentic engineering principles to optimize Google's CoreOS compute infrastructure. Responsibilities include conceptualizing AI strategies, building tools for kernel quality insights, managing fix rollouts, designing tests, debugging kernel issues, and providing technical leadership. The role involves a mix of exploration, engineering, and productionization, aiming to revolutionize how CoreOS is worked on, tested, released, and supported using AI.

UX Engineer for Robot Infrastructure at DeepMind, focusing on human-robot interaction, teleoperation, and collaboration with autonomous agents. The role involves architecting full-stack web applications for robotics fleet management and ML training data systems, partnering with ML researchers and engineers to create seamless user experiences, and adapting to emerging AI capabilities.

Manager for engineering teams building and deploying AI infrastructure for Google Distributed Cloud and Sovereign Cloud, focusing on GenAI, air-gapped runtimes, and optimizing inference performance in regulated environments.

Engineering Manager for ML Infrastructure, focusing on fleet-wide scheduling for Alphabet's ML workloads. This role involves leading a team, setting technical roadmaps, and ensuring efficient, reliable, and easy-to-use scheduling for ML tasks across production machines, supporting services like Vertex AI and Gemini models.