Manager of a GenAI Forward Deployed Engineering (FDE) team responsible for leading AI/ML engineers to deploy bespoke agentic solutions within customer environments. The role involves technical mentorship, strategic alignment with Product, Engineering, and Sales, and resolving production-level obstacles for AI adoption in enterprise settings.

Manager of a GenAI Forward Deployed Engineering (FDE) team responsible for leading AI/ML engineers in deploying bespoke agentic solutions within customer environments. The role involves technical mentorship, strategic alignment with Product, Engineering, and Sales leadership, and resolving production-level obstacles related to AI adoption.

Software Engineer III, AI/ML Cloud role at Google, focusing on building and deploying scalable AI/ML platform capabilities for Google Cloud customers. The role involves engineering solutions for LLM serving and tuning, ensuring reliability, performance, and quality, and implementing guardrails and safety gates for the Vertex AI organization. It requires experience in ML infrastructure, model deployment, and potentially speech/audio or reinforcement learning.

Staff Applied AI Agent Engineer for Google Cloud Platform, focusing on deploying and optimizing Generative AI agents for enterprise customers. The role involves partnering with customers, designing and co-developing AI solutions, creating reusable tools, and potentially contributing to the core product codebase. It requires significant software development experience and expertise in ML infrastructure, model deployment, and data processing.

Software Engineer on the Acceleration Platform Team building scalable, AI-native agentic systems to automate complex workflows and solve enterprise-scale engineering problems. The role involves leading zero-to-one initiatives, defining AI-first engineering best practices, scaling evaluations and guardrails for AI safety, and building advanced telemetry for debugging and optimizing self-supporting behaviors.

Software Engineer on the Acceleration Platform team in Singapore, responsible for designing and implementing AI-native agentic systems to eliminate developer toil. The role involves leading zero-to-one technical initiatives, building scalable frameworks for self-sustaining AI at an enterprise scale, and mentoring junior peers. Responsibilities include designing systems where AI agents reason and execute workflows, blending traditional software development with prompt engineering and RAG, creating evaluation pipelines for AI performance, and troubleshooting non-deterministic AI behaviors.

Google is seeking a Senior Software Engineer for the YouTube Ads ML team. This role involves applying state-of-the-art machine learning techniques to deliver ad recommendations on YouTube by analyzing user activity sequence patterns. The engineer will create personalized advertising experiences, identify high-value users for advertisers, and research, design, apply, and launch innovative ML techniques. The role requires strong software development skills, experience with ML infrastructure, and Python programming.

Technical Lead Manager for ML and GenAI in Ads Safety at Google. This role involves managing a team of engineers focused on enhancing and rolling out ML models, solving bottlenecks, and architecting production-quality AI-powered products, including recommendation systems and potentially Generative AI Agents. Requires experience in building AI-powered products with technologies like RAG and managing ML systems in production.

Software Engineer II at Google Threat Intelligence focusing on developing and deploying AI-driven solutions, including LLMs and AI agents, for security-related use cases. The role involves research, design, implementation, evaluation, and full lifecycle contribution to AI-powered features.

Senior Forward Deployed Engineer for Google Cloud's Applied AI organization, focusing on designing, developing, and deploying AI agents and solutions for enterprise customers. The role involves close customer partnership, coding, custom tooling development, and providing feedback to core product teams. It requires experience with Generative AI concepts and ML infrastructure, aiming to scale AI adoption within the Google Cloud ecosystem.

This role focuses on building platforms for specialized agents that coordinate to manage commerce intents at scale, pushing AI search boundaries for seamless visual and text experiences. It involves pioneering self-optimizing systems and building/deploying recommendation systems models, utilizing ML infrastructure, and addressing AI quality problems with agentic solutions.

Staff Software Engineer focused on optimizing GPU performance for LLM training and serving within Google Cloud. This role involves benchmarking, performance analysis, and implementing solutions at scale, working with cutting-edge AI accelerators and low-level GPU programming.

Software Engineer III, GenAI, Google Cloud, focusing on integrating Google Search and private data into LLMs for intelligent solutions on Vertex AI. Responsibilities include building grounding systems, improving LLM grounding algorithms, and developing search ranking improvements. Requires experience in GenAI, LLMs, and Agentic AI Systems.

Senior Software Engineer role focused on building the core reasoning engine for a generative AI-powered data analytics platform (BigQuery). The role involves technical strategy, architectural design, cross-functional collaboration with AI/ML teams, and ensuring the performance, reliability, and observability of agent services. It requires experience with ML infrastructure, GenAI techniques, agent development, distributed systems, and data warehousing.

Senior Software Development Manager for ML Infrastructure within Core Infra at Google, focusing on GenAI projects. The role involves leading teams, setting technical direction, and contributing to system design and code for GenAI-focused initiatives, including model deployment, evaluation, and fine-tuning.

Senior Software Engineer role focused on designing and implementing GenAI solutions within Google Cloud Compute Infrastructure. The role involves leveraging ML infrastructure, evaluating techniques, and working with state-of-the-art GenAI models like LLMs and Large Vision Models. Requires strong programming skills (Python/C++), experience with ML infrastructure, and software design/architecture.

Staff Software Engineer at Google working on AI/ML for YouTube Ads, focusing on composing, personalizing, and optimizing ad creatives at scale using deep learning, reinforcement learning, and generative AI. The role involves developing intelligent systems, building ML pipelines, exploring generative models for various media, and contributing to the architecture of centralized services for creative optimization.

Lead an engineering team developing on-device machine learning models and ML pipelines for smart home cameras, managing the full lifecycle of AI-powered features with a focus on performance, power, latency, and thermal constraints on resource-constrained hardware. Responsibilities include driving ML deployment pipelines, managing trade-offs between model performance and hardware, and maintaining high engineering standards for C++ development in an embedded context.

Senior Software Engineer role focused on building and optimizing AI-driven personalization and recommendation systems for Google Search and Discover. The role involves developing new ranking algorithms, analyzing experiment results, designing recommendation system models, and leveraging ML infrastructure to influence what millions of users see daily. It requires significant experience in building and deploying recommendation systems models and ML infrastructure in production.

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.

This role focuses on ensuring the safety and trustworthiness of Google Cloud's AI products. The Senior Engineering Analyst will leverage advanced ML/AI techniques to develop and deploy scalable safety solutions, analyze AI risks (including generative and agentic AI), and respond to security incidents. The role involves identifying and mitigating emerging threats, synthesizing data to uncover abuse patterns, and partnering with engineering and product teams to combat novel AI threats.

Software Engineer role focused on implementing Generative AI solutions within Google's Geo Consumer products. This involves writing code, collaborating on design and reviews, triaging issues, and contributing to GenAI solutions using ML infrastructure. The role requires experience with building and deploying generative model applications, prompt engineering, prompt tuning, and post-training evaluation, as well as familiarity with state-of-the-art GenAI techniques like LLMs and Multi-Modal models.

Manager of a Generative AI Forward Deployed Engineering (FDE) team, leading AI/ML engineers to bridge the gap between AI products and production-grade reality within customers. The team codes, debugs, and jointly deploys bespoke agentic solutions directly within customer environments. Responsibilities include technical mentorship, managing alignment with Product/Engineering/Sales, resolving production-level obstacles (data readiness, integration, state-management), leading technical hiring, identifying skill gaps in emerging tech (MCP, tool-calling, foundation models), and collaborating with product/engineering to translate field insights into roadmaps.

Senior Software Engineer to work on an ML-as-a-service platform that enables Google product teams to build and launch GenAI-powered products. The role involves developing and maintaining production services, improving ML fleet efficiency, and implementing customer-requested ML/AI features, with a focus on prompt optimization, fine-tuning, and hyperparameter optimization.

Senior Staff Software Engineer at Google, focusing on AI/ML for Google Workspace products. The role involves designing, developing, and deploying large-scale AI/ML solutions to enhance productivity tools like Gmail, Docs, and Meet. Responsibilities include technical leadership, ML infrastructure optimization, and driving technical project strategy, with a focus on shipping AI-powered features to billions of users.

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.

Software Engineer for Gemini Live, a multimodal AI assistant destination focused on delivering natural, responsive, and personalized conversational experiences for users across various daily tasks. The role involves defining and driving the architecture for integrating Gemini Live, engineering multimodal experiences, developing non-verbal communication systems for low-latency performance, and partnering with GenAI/Model teams to integrate advanced capabilities and quality rubrics.

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.

This role is for a Senior Software Engineering Manager to lead a team building a Security Agentic Platform and AI-driven security agents for Google Cloud Security Operations. The focus is on developing and deploying agentic AI for security products, managing technical strategy, and overseeing the end-to-end development lifecycle.

Senior Software ML Engineer focused on Gemini Enterprise, responsible for engineering systems that define intelligence, reliability, and helpfulness. This includes architecting automated evaluation frameworks, designing optimization algorithms, and solving technical issues at the intersection of LLMs and enterprise-grade software. The role involves leading the technical development of agentic features, designing and implementing GenAI solutions, leveraging ML infrastructure, and evaluating tradeoffs between techniques.

Lead Software Engineer focused on infrastructure quality for robotics, including designing and implementing large-scale software and hardware systems, leading agentic AI initiatives, and driving system reliability for fleet management and data systems. The role involves managing releases, defining engineering productivity metrics, and optimizing the Data/ML Flywheel.

Senior Software Engineer to build next-generation modeling and quality infrastructure for queryless ad formats, using LLM-based distillation and differential modeling. Will lead technical roadmaps across retrieval, auction, and measurement, and develop evaluation frameworks where LLMs simulate user personas to predict ad quality. Focus on personalization and implicit user intent in local discovery.

Software Engineer III, AI/ML role focused on designing and iterating on agentic flows for user intent extraction, query generation, content retrieval and synthesis, and multi-modal generation within Google's Discover personalized content recommendation feed. The role involves conducting applied research, building quality intuitions, defining evaluation metrics, integrating new content formats, and implementing ML solutions at production scale.

Software Engineering Manager II for Google Cloud AI GenAI team, focusing on leading engineering teams, setting technical vision, and guiding the design and optimization of GenAI solutions, ML infrastructure, and data preparation strategies. The role involves people management, technical leadership, and contributing to product strategy within the AI Research team that aims to push state-of-the-art AI and collaborate with product teams.

Staff Software Engineer focused on optimizing the performance of ML models (including Gemini and OSS models) on TPU systems for both JAX and PyTorch platforms. The role involves identifying and maintaining ML benchmarks, analyzing performance metrics, and collaborating with compiler and runtime teams to improve performance. It also includes engaging with product teams and researchers to solve performance problems for large-scale ML training and serving.

AI/ML Engineer for Google Public Sector, focusing on productionizing AI solutions for national security customers. The role involves acting as a technical advisor, designing and implementing AI architectures, and coaching customers on ML systems. Requires experience with ML frameworks, coding, and a Top Secret/SCI clearance.

Staff Applied AI Agent Developer role focused on applying Generative AI (Gemini Enterprise) to solve real-world challenges for strategic customers. Responsibilities include designing, co-developing, debugging, and deploying custom conversational AI agents, writing bespoke code, developing custom tooling, and providing technical guidance to customers. The role also involves creating reusable tools, building documentation, and influencing product strategy based on field insights.

Staff Software Engineer focused on integrating Generative AI into Google Discover's personalization feed. The role involves architecting LLM integration layers, owning prompt engineering, evaluation, observability, and leading model selection/fine-tuning. The goal is to evolve Discover into a conversational and co-creative personal companion, impacting billions of users.

Senior Staff Forward Deployed Developer role focused on applying Google's Generative AI to customer problems, building and deploying AI agents on the Customer Engagement Suite platform. Responsibilities include understanding customer needs, designing and co-developing AI solutions, creating reusable tools, and optimizing ML infrastructure.

Senior engineer to architect and build Generative AI solutions for enterprise customers using Gemini and Vertex AI, focusing on agentic workflows and semantic data layers. The role involves resolving technical hurdles, optimizing latency, bridging systems, and transforming bespoke solutions into reusable assets and reference architectures. This includes mentoring engineers and advising customer CTOs, with a strong emphasis on customer engagement and product incubation.

Senior Software Engineer focused on AI/ML for Google Search Quality, involving development of ML models, leveraging ML infrastructure, and working with large-scale data processing and serving systems, particularly for abuse detection and search ranking.

Senior Software Engineering Manager for Google's AI and Infrastructure team, focusing on leading teams, setting technical direction, and overseeing the development and deployment of large-scale AI and ML infrastructure. The role involves managing engineers, defining product strategy, optimizing ML infrastructure, and driving technical projects across various ML specializations.

Staff Software Engineer, Machine Learning, Discover Ads Retrieval. This role focuses on innovating and defining the retrieval strategy for Google's Discover Ads, connecting users with relevant ads in their feed. The engineer will lead ML engineers to explore frontiers in embedding-based retrieval, deep learning architectures, and multi-objective optimization, impacting billions of users globally. The work involves moving beyond legacy retrieval methods to design next-generation applicant generation strategies and integrate fresh signals into retrieval models.

This role focuses on building and evaluating AI agents to classify web pages and reduce operational costs for Google's Safe Browsing system. It involves data analysis to identify harmful entities, understanding malicious website behavior using LLMs, and collaborating with anti-abuse teams to fight phishing and malware at scale. The role requires experience with AI agentic workflows and a strong background in data analysis and programming.

Staff Software Engineer on the AI and Infrastructure team at Google Cloud, focusing on delivering AI and Infrastructure at scale. Responsibilities include designing, developing, and maintaining large-scale software solutions, providing technical leadership, and leading the design and implementation of solutions in specialized ML areas, optimizing ML infrastructure, and guiding model optimization and data processing strategies. Requires experience in software development, ML infrastructure, and ML design optimization.

Google is seeking an Engineering Manager for their Agentic Planning and Memory team, focused on transforming Google Workspace into a proactive digital partner. The role involves leading teams to develop advanced function-calling capabilities for autonomous workflow execution and building an agentic memory layer for improved context retention and utilization. This position requires strong technical leadership, experience in ML infrastructure, and expertise in GenAI techniques to impact billions of users.

Staff Software Engineer for Gemini Live, a multi-modal AI assistant aiming to be a daily habit for users seeking advice, information, and learning experiences. The role focuses on defining and driving the front-end architecture, engineering an intuitive multi-modal experience, and ensuring low-latency performance for a responsive and natural AI interaction. This involves partnering with GenAI and Model teams to integrate advanced capabilities and establish quality metrics.

Tech Lead for YouTube Shorts Discovery, focusing on ML Recommendations. This role involves designing, developing, and deploying large-scale software solutions and ML infrastructure to drive the success of YouTube Shorts. The primary focus is on building audience identification systems within the recommendation stack, leveraging advanced modeling techniques. The role requires technical leadership, managing project priorities, and guiding the development of ML models and data processing strategies.