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.

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 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.

Software Engineer III role focused on enabling and optimizing foundational AI/ML models (LLMs, Diffusion) within Google Cloud infrastructure, specifically using frameworks like vLLM and MaxText. The role involves partnering with customers to measure model performance, identify technical bottlenecks, collaborate with infrastructure teams, and design specialized ML solutions. It requires experience with ML infrastructure, GenAI concepts, and debugging training/inference workloads.

Senior AI Software Engineer role focused on leading the design, development, and deployment of AI/ML systems for HR applications at Google. This role involves technical leadership, mentoring, collaboration, and driving the adoption of AI technologies to optimize HR processes and employee experiences.

Senior Software Engineer role focused on designing and implementing GenAI solutions within Google Ads, leveraging ML infrastructure and state-of-the-art GenAI techniques like LLMs and Multi-Modal models. Requires strong programming skills, experience with ML infrastructure, and a solid understanding of GenAI concepts.

This role focuses on designing and architecting next-generation Tensor Processing Units (TPUs) for AI/ML workloads. Responsibilities include defining architecture, developing power/performance models, RTL design, and collaborating with hardware, software, and ML teams for effective hardware/software co-design. The role also involves using AI techniques for physical design and optimizing silicon bring-up processes.

Senior Software Engineer on the Server AI Foundations team, focusing on building AI-powered tools for Google developers to enhance productivity and integrate AI into workflows. The role involves technical leadership in design, architecture, and implementation of AI-integrated solutions within Google's production platform infrastructure.

This role focuses on the design and implementation of Application-Specific Integrated Circuits (ASICs) for accelerating Machine Learning (ML) computations in data centers, specifically for Google's AI and Infrastructure team. The engineer will work on micro-architecture, implementation, and optimization of these custom silicon solutions, collaborating with various teams to deliver high-performance and efficient hardware accelerators.

This role focuses on defining and implementing safety strategies for generative AI systems, including developing evaluation paradigms, guiding engineering and research teams on safety mitigations like fine-tuning and guardrails, and analyzing the AI threat landscape to create a proactive mitigation agenda. The role is critical for ensuring AI safety is a foundational component of Google's AI systems.

This role focuses on building Agentic User Interface (UI) flows for Large Language Model (LLM) journeys, collaborating with UX and researchers to democratize AI techniques and improve end-to-end user experiences for Google Cloud's Generative AI features.

Application Engineer role focused on building Generative AI and LLM-based applications and agents, integrating them into web applications, and supporting sales and supply chain processes within the Google Devices & Services team. Requires strong software development skills and experience with AI/ML technologies.

This role focuses on designing and developing AI-powered solutions and prototypes for enterprise customers on Google Cloud Platform. The Solutions Acceleration Architect will lead technical relationships with partners, build trusted advisory relationships, and define technical architectures for AI initiatives including fine-tuning and RAG. The role involves showcasing the potential of data and AI to solve business challenges and contributing to industry thought leadership.

Engineering Director to lead the technical and architectural reinvention of the Knowledge Catalog platform, integrating Generative AI as a core competency for autonomous data management and governance. Focus on defining AI-first roadmaps, managing LLM integration, and ensuring high-quality data for AI/ML models.

Staff Software Engineer for Google Cloud's AI/ML Infrastructure team, focusing on building and operating a multi-tenant ML-as-a-service platform to enable Google product teams to build and launch GenAI-powered products. The role involves simplifying AI workflows, collaborating across front-end, infrastructure, and modeling expertise, and democratizing AI techniques.

Customer Engineer focused on AI infrastructure modernization using Google Cloud's TPU/GPU accelerators. The role involves guiding customers on architecture, deployment, and optimization of large-scale training and inference jobs, working with AI/ML accelerators, and supporting sales teams in piloting and deploying these solutions.

This role involves designing and implementing machine learning solutions for enterprise customers on Google Cloud, acting as a trusted technical advisor, and coaching customers on production ML systems. It requires experience with ML solutions, cloud enterprise solutions, and coding in general-purpose languages, with a preference for recommendation engines, data pipelines, and deep learning frameworks.

Staff Software Engineer for Google Cloud Networking Security team in Bangalore, focusing on building and operating large-scale network security services. The role involves defining technical strategy, leading the implementation of AI/ML features for threat detection and automated responses, and providing technical guidance and mentorship. Requires experience in software development, network security, distributed systems, cloud, and AI/ML.

Senior Staff Software Engineer role at Google, focusing on Search Intelligence. The role involves technical leadership, designing, developing, and enhancing large-scale software solutions, collaborating with AI/ML researchers and Product Managers, and ensuring the reliability and scalability of Search Intelligence features for the Indian market. Requires 8 years of software development experience and experience in technical leadership.

Software Engineering Manager for Google Cloud's Database Intelligence Platform team, focusing on delivering AI-powered database management, AI-assisted journeys, and intelligent agents for monitoring and troubleshooting. The role involves technical leadership, team management, and collaboration across multiple database teams within GCP.

Technical Solutions Engineer for Google Cloud AI/ML portfolio, focusing on customer-reported issues, deployment failures, and model performance degradation. Responsibilities include troubleshooting, debugging ML models (TensorFlow, PyTorch) in production environments (Kubernetes, Compute Engine), and ensuring production readiness of generative AI models. Requires Python coding, AI/ML concepts, and networking/system administration experience.

Staff Software Engineer at Google, focusing on Search Intelligence. The role involves designing, developing, and deploying software solutions to improve the quality of AI-generated content within Google Search. This includes implementing and experimenting with AI/ML models, analyzing performance, and managing open-ended problems in large-scale systems. The position requires experience in AI platform and ML infrastructure, with a focus on improving AI-generated content quality and system health.

Staff Software Engineer role focused on defining strategy and developing solutions for agentic cloud use cases within Google Cloud. Requires strong software development, design, and architecture experience, with a preference for experience in building agentic systems.

Technical Solutions Engineer for Google Cloud AI/ML portfolio, focusing on customer-facing support, troubleshooting ML deployments (including Generative AI), and ensuring production readiness. Requires strong Python scripting, debugging skills, and experience with ML frameworks and cloud infrastructure.

This role is for a Data Science Manager to lead a team in India focused on AI/ML initiatives for People Operations. The manager will provide technical leadership, oversee the development and deployment of AI/ML models (including NLP and predictive models), and bridge the gap between business needs and technical execution. The role involves hiring, mentoring, and managing the data science pod, driving technical architecture, and advocating for AI transformation within the organization.

This role focuses on ensuring the safety and trustworthiness of AI features within Google Photos, specifically generative AI. The Senior Engineering Analyst will work with various teams to develop and execute comprehensive evaluations, identify emerging risks and abuse vectors, and build resilience against malicious inputs. The role involves defining testing approaches, tools, and solutions, establishing testing to discover risks, and defining program metrics and feedback loops.

Staff Software Engineer role at Google Cloud focusing on AI and ML, specifically in building AI Agents, Agentic AI, and ML models with NLP capabilities for security products. The role involves leading a full-stack team, designing, developing, testing, and deploying platforms, and collaborating with various stakeholders.

Staff Software Engineer role focused on building applied AI products and developer infrastructure for YouTube, with an emphasis on Generative AI tools and multi-modal agents to improve the development process.

Staff Software Engineer role focused on building AI for developers within Google Search, leveraging agentic frameworks and LLM-powered automation to enhance developer experience and build scalable platform systems.

Software Engineer role focused on building AI-based agents and a full-stack application for workflow automation within the AI and Infrastructure organization at Google Cloud. The role involves defining requirements, leading development, and implementing features to automate core tasks and improve program delivery.

Technical Program Manager to prototype AI agents for supply chain optimization within Google Cloud. The role involves analyzing business requirements, designing and building AI agents, collaborating with data science and engineering teams, and leading a technical program management team. Requires experience in supply chain operations, leadership, prompt engineering, classical ML, and generative AI.

Software Engineer role focused on implementing ML solutions, utilizing ML infrastructure, and contributing to model optimization and data processing. Requires experience in software development and ML infrastructure, with preferred qualifications in C++ and software design.

Staff Software Engineer role focused on building Search for Commerce, including traditional search and agentic AI discovery experiences. The role involves developing scalable product search solutions and conversational agents for enterprises, leveraging ML infrastructure and collaborating with model builders.

Software Engineer III on the AI and Infrastructure team at Google Cloud, focusing on delivering AI and Infrastructure at scale. The role involves writing product/system code, collaborating on design and code reviews, contributing to documentation, triaging and debugging issues, and implementing solutions in ML areas including ML infrastructure, model optimization, and data processing. Requires experience in Python/C++, ML infrastructure (deployment, evaluation, optimization, data processing), and optionally speech/audio or reinforcement learning.

Google is seeking a PhD Software Engineer with expertise in AI/ML and large-scale distributed systems to design, test, deploy, and maintain software solutions for AI and Infrastructure (AI2) organization. The role involves defining technical goals, developing scalable systems, applying research expertise to complex problems, and contributing to essential Google services and Cloud products.

This role focuses on the design and verification of AI/ML hardware accelerators (TPUs), involving architecture definition, performance modeling, RTL design, and hardware/software co-design. The engineer will work on optimizing ML workloads and developing efficient design verification strategies for next-generation TPUs, leveraging AI techniques for physical design convergence.

Software Engineering Manager II for Google Cloud's AI and Infrastructure team, focusing on delivering AI and Infrastructure at scale. The role involves technical leadership, team management, setting priorities, developing roadmaps, and guiding system designs, with a focus on enabling advanced AI models and delivering computing power.

Software Engineer with a PhD, focusing on AI/ML infrastructure and systems within Google Cloud. The role involves writing product/system development code, participating in design reviews, reviewing code, contributing to documentation, triaging and debugging complex technical issues, and collaborating on design, analysis, and development across the stack. The focus is on building and scaling AI/ML capabilities on Google's frameworks and infrastructure, contributing to products used by billions.

Silicon Architecture/Design Engineer focused on developing next-generation TPUs for AI/ML workloads. Responsibilities include workload characterization, architecture specification, power/performance modeling, RTL design, hardware/software codesign, and leveraging AI techniques for physical design. The role requires a PhD and experience with accelerator architectures and data center workloads.