Senior Software Engineer to architect and build agentic infrastructure for unifying fragmented business domains, enabling agents to perform multi-hop reasoning and tool execution using RAG and LLM orchestration for customer context and autonomous action plans.

Senior Engineering Manager for ML Infrastructure in Ads Safety, leading technical strategy and organizational growth for platforms powering high-stakes content and actor detection. Bridges ML research and production engineering, driving evolution of ML infrastructure for complex models and operational excellence.

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.

Google is seeking an Engineering Manager for their ML Infrastructure Control Plane team. This role involves leading engineering efforts for Alphabet's ML workloads, supporting critical missions across various Google divisions. The team focuses on providing efficient, reliable, and easy-to-use fleet-wide scheduling for ML infrastructure. The manager will set team priorities, develop technical roadmaps, guide system designs, and oversee code development and reviews, ensuring the efficient operation of large-scale ML infrastructure.

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.

Technical Program Manager for Generative AI Safety at Google, focusing on leading initiatives to expand content safety infrastructure, integrate safety classifiers, and build rapid response capabilities for AI abuse. The role involves partnering with cross-functional leaders to convert threat intelligence into scalable models and technical protections within the serving stack, orchestrating safety engineering teams, and managing global workflows for timely integration and evaluation of safety models for Gemini releases. This role also coordinates with infrastructure teams, generative AI product groups, and foundational model researchers to integrate safety signals into primary models.

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 focused on building ML compilers for EdgeTPU hardware, optimizing ML models for inference, and working on hardware/software co-optimizations. Collaborates with ML model developers and researchers to deploy models on EdgeTPU.

Google is seeking a Staff Software Developer to join their Conversational Agents team, focusing on building and serving large-scale chat and voice bots. This role involves technical leadership, influencing a distributed team, and designing/developing/deploying large-scale software solutions for AI-driven conversational agents. The team is part of the rapidly growing Cloud AI product suite, transforming enterprise customer connections through AI.

Software Engineer role focused on developing and optimizing compilers for Google's EdgeTPU, a custom ML accelerator for on-device AI. The role involves analyzing compiler performance, enhancing parallelization algorithms, and efficiently mapping generative AI models to EdgeTPU instructions to enable cutting-edge ML experiences on devices like Pixel phones.

Senior Software Engineer focused on optimizing AI/ML infrastructure performance across the technical stack, from networking and data storage to ML models, to provide AI developers with a high-performance experience on Google's AI infrastructure. Responsibilities include designing and implementing solutions, optimizing performance, profiling, debugging, and developing tools for AI/ML infrastructure.

Software Engineer III role focused on building and integrating Cloud Compute software to bootstrap TPU AI Infrastructure, including OS image deployment and node-specific software for computation offload, integrating with TPU clusters and cloud infrastructure. The role involves collaboration with TPU Software and Hardware teams and partnering with cross-functional leaders to shape ML infrastructure.

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 Engineering Manager for Emergent AI Infrastructure at Google, focusing on building and managing teams that deliver AI infrastructure at scale with sophisticated security and locality requirements for enterprise customers. The role involves technical leadership, people management, and contributing to product strategy for AI platforms and services.

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.

Tech Lead for Google Kubernetes Engine (GKE) AI Platform, focusing on managing containerized AI/ML workloads on GPU/TPU infrastructure using Kubernetes. The role involves driving innovation in reliability, efficiency, and scale of AI infrastructure, engaging with customers, and leading technical direction for workload optimization.

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.

Senior Software Engineer role focused on building AI/ML features for Google Workspace products, impacting billions of users. The role involves designing and implementing ML solutions, leveraging ML infrastructure, and collaborating with model builders from Google DeepMind to shape the future of productivity tools.

This role focuses on RTL design for AI/ML hardware accelerators, specifically Google's TPUs. The engineer will design and verify complex digital designs, focusing on TPU architecture and its integration within AI/ML systems, contributing to the innovation behind Google's AI/ML applications.

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.

This role focuses on RTL design for AI/ML hardware acceleration, specifically TPUs, powering Google's AI/ML applications. The engineer will design and verify complex digital designs, focusing on TPU architecture and its integration within AI/ML systems, contributing to custom silicon solutions.

Staff Software Engineer focused on optimizing the performance and efficiency of Google's TPU fleet for Machine Learning training and serving workloads, including models like Gemini. This role involves deep analysis of performance metrics, collaboration with product teams and researchers, and implementation of solutions at scale, potentially touching compiler, runtime, model co-design, quantization, and sparsity.

Engineering Manager for Google BigQuery's Advanced Analytics team, focusing on the AI, ML, Search, and extensibility architecture. The role involves developing a technical roadmap for the extensibility platform, enabling custom logic execution within BigQuery for AI/ML pre-processing, training, and inference. It also includes leading feature lifecycles, driving technical vision for hybrid compute workloads, and overseeing production stability and performance.

Software Engineer III, AI/ML role focused on developing LLM-based tools for generating synthetic user data and conversations for health and home feature evaluations. This involves implementing ML solutions, utilizing ML infrastructure, and contributing to model optimization and data processing, with a focus on advancing the quality and realism of synthetic context and defining evaluation metrics.

Customer Engineer II, Applied AI, Google Cloud. This role involves partnering with technical sales teams as an Applied AI subject matter expert to help customers understand and leverage Google Cloud's Generative AI solutions, particularly for customer experience applications. Responsibilities include engaging with customers, understanding their business and technical requirements, developing cloud solutions, conducting Proofs of Concept, and troubleshooting technical issues related to Google's first-party AI offerings. The role requires expertise in conversational AI, building or leveraging AI solutions/ML APIs, and presenting practical solutions to technical and executive stakeholders.

Senior Staff Software Engineer for Google Slides, focusing on integrating GenAI features. This role involves overseeing technical strategy, leading development of AI-powered features using Gemini and Nano Banana, and collaborating with Google DeepMind. The goal is to enhance presentation creation through AI-powered tools, impacting billions of users.

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.

Senior Software Engineer role focused on AI/ML within Google Search, involving the design and implementation of ML solutions, leveraging ML infrastructure, and expertise in specialized ML areas like speech/audio or reinforcement learning. The role requires experience in programming, software development, and ML infrastructure aspects such as deployment, evaluation, optimization, data processing, and debugging.

Software Engineer role focused on building and scaling content safety platforms using ML infrastructure and responsible AI techniques to protect users from harmful content. The role involves designing, building, and maintaining these platforms, ensuring quality implementations of company-wide standards for Responsible AI, and collaborating with stakeholders. It requires experience in software development, ML infrastructure, and potentially speech/audio or reinforcement learning.

Software Engineer role focused on designing, building, and maintaining content safety solutions for Google's business-critical products. This involves implementing Responsible AI standards, protecting users from harmful content using ML/AI techniques, and ensuring quality through classifiers and classifiers. The role requires production-grade experience in serving infrastructure and product integrations, with a focus on delivering scalable and future-proof solutions.

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.

Software Engineer III at Google Workspace focused on implementing GenAI solutions for productivity tools like Gmail, Docs, and Meet. The role involves utilizing ML infrastructure, contributing to data preparation, optimization, and performance enhancements, and working with core GenAI concepts such as LLMs, Multi-Modal, and Large Vision Models for text, image, video, or audio generation. The primary goal is to build AI-powered features into user-facing products.

Senior Software Engineer focused on building and deploying custom conversational AI agents for enterprise customers on Google Cloud's Customer Engagement Suite. This role involves direct customer partnership, designing, developing, and optimizing AI solutions, and contributing to core product improvements. The role emphasizes problem-solving, creating reusable tools, and potentially optimizing ML infrastructure and data processing.

Senior Software Engineer role focused on building and deploying recommendation systems, rankings, and predictions models within Google Ads, leveraging ML infrastructure and contributing to architecture design. Requires significant experience in building and deploying recommendation systems and ML infrastructure in production.

Software Engineer III, AI/ML, GenAI at Google. This role involves writing product or system development code, collaborating with peers, contributing to documentation, triaging issues, and implementing GenAI solutions. It requires experience with ML infrastructure, GenAI techniques like LLMs and LVMs, and machine learning frameworks like TensorFlow. The position is focused on engineering and scaling GenAI capabilities within Google's products.

Senior Software Engineer at Google's YouTube, focusing on AI/ML development. The role involves writing and testing code, collaborating with stakeholders, contributing to documentation, triaging and debugging issues, and designing/implementing solutions in specialized ML areas using ML infrastructure. Requires experience in Python, C++, software design, and specific ML fields like speech/audio, reinforcement learning, or ML infrastructure.

Senior Software Engineer on Google Cloud Compute focusing on ML/AI algorithms, deep learning, and NLP. Responsibilities include software development, design, testing, deployment, and maintenance, with a focus on managing project priorities and deliverables. Requires 5 years of software development experience and 3 years of experience with ML/AI algorithms and tools.

Software Engineer role focused on developing and optimizing the TPU compiler for large-scale machine learning models. This involves writing C++ code, designing performance optimizations, and applying AI techniques to the compiler itself. The role supports both internal Google teams (like DeepMind) and external Google Cloud customers.

Senior Software Engineer focused on optimizing GPU performance for Google's AI models and products. This role involves low-level GPU programming, compiler optimizations, and influencing the GPU software stack and fleet deployment to ensure top performance for ML workloads.

Software Engineer III, AI/ML role at Google YouTube, focusing on implementing ML solutions, utilizing ML infrastructure, and contributing to model optimization and data processing. Requires experience in Python/C++, ML infrastructure, and potentially speech/audio or reinforcement learning.

Software Engineer III on the Google Cloud AI Research team, focusing 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, triaging issues, and debugging. Requires experience in Python/C++, and ML infrastructure such as model deployment, evaluation, optimization, and data processing. Experience with speech/audio or reinforcement learning is a plus.

This role focuses on developing architectural and micro-architectural models for next-generation TPUs (Tensor Processing Units) to enable quantitative analysis of performance and power. The engineer will contribute to Machine Learning workload characterization, benchmarking, and hardware-software co-design, collaborating with various teams to define TPU chip specifications and roadmaps for AI/ML hardware acceleration.

Software Engineer III at Google working on AI/ML Recommendations, Rankings, and Predictions for YouTube. The role involves writing product/system code, collaborating with peers, contributing to documentation, triaging issues, and building/deploying recommendation systems models using ML infrastructure, with a focus on model optimization and data processing. Requires a Bachelor's degree, 2 years of Python/C++ experience, 1 year of experience building/deploying recommendation systems, and 1 year of ML infrastructure experience.

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.

Staff Software Engineer at Google working on AI/ML for YouTube Recommendations, Rankings, and Predictions. The role involves designing, developing, and deploying large-scale software solutions, providing technical leadership, and optimizing ML infrastructure. Key responsibilities include leading the design and implementation of recommendation systems, optimizing ML infrastructure, and guiding model architecture development. Requires significant experience in building and deploying recommendation systems models in production and leading ML design and optimization.