Google

Senior Software Engineer focused on building and deploying recommendation systems models for YouTube, leveraging ML infrastructure and contributing to architecture design. This role involves coding, testing, debugging, and designing models for retrieval, prediction, ranking, and personalization.

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.

Software Engineer role focused on implementing and designing Search features, leveraging advanced GenAI capabilities and LLM concepts, with a focus on Kubernetes-based infrastructure for scalability and performance.

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.

Software Developer for Android Glasses System UI, focusing on creating user-centric experiences and foundational platform components, including AI agent interfaces, dynamic widgets, and novel interaction methodologies for augmented reality. Collaborates with ML perception specialists and translates user needs into prototypes.

Software Engineer to build and deploy AI-powered CI infrastructure for Android, Chrome, and ChromeOS. Focus on scalability, reliability, and streamlining operational workflows using Agentic AI.

This role focuses on power modeling for Google Pixel devices, optimizing battery life and power efficiency by developing methodologies, simulation tools, and data analytics. The engineer will influence hardware decisions based on AI workload simulations and real-world user behavior, impacting millions of users. The role involves designing power modeling methodologies, processing device analytics, creating subsystem models, building visualization tools, and projecting power impacts of future features.

Google is seeking an engineer to work on infrastructure for AI-powered Workspace products, focusing on developing and enhancing software solutions that will shape the future of productivity tools. The role involves managing project priorities, designing, developing, testing, deploying, and maintaining software, with a focus on large-scale infrastructure and distributed systems, and collaborating with AI model builders.

Manage an engineering team responsible for implementing various software products and designing and building internal applications that support internal business processes related to supply chain and engineering operations. Leverage Artificial Intelligence/Machine Learning (AI/ML) to solve supply chain problems.

This role focuses on leveraging emerging technologies, including machine learning, to build and scale innovative technical solutions for Google's largest advertising clients and partners. The primary responsibility is to adapt and scale existing solutions, automate workflows, and manage the full lifecycle of these scaled solutions to drive customer growth and enhance ad experiences.

Google is seeking a Data Center Analytics Engineer to design and implement advanced analytics, AI/ML integrations, and data visualizations. The role involves owning data engineering workstreams, collaborating on custom web applications, and engaging with stakeholders to solve business problems. The position requires a Bachelor's degree in Computer Science or equivalent experience, with 5 years in analytics and data science applications, and 5 years in data engineering. Experience with Machine Learning and AI Integrations, and web development are preferred.

This role focuses on architecting camera systems, graphics, video, and display pixel processing for AR/XR products, aiming to accelerate the adoption of spatial computing. The position involves defining end-to-end pixel processing pipelines, from sensor to output for human or AI consumption, and collaborating with various partners. While the role touches upon AI and computer vision, its core is in hardware and system architecture for XR devices, not direct AI model development.

This role is for a Senior Software Engineer on the Google Compute Engine (GCE) team, focusing on building and optimizing the foundational infrastructure for AI/ML workloads. The engineer will lead the introduction of new VM families, analyze and optimize VM performance, develop software components for reliability and performance, and provide engineering support for existing VM families. The role requires experience with IaaS, large-scale infrastructure, distributed systems, and virtualization, with a focus on supporting the growing demand for AI/ML computing.

Data Engineer role focused on designing and managing data pipelines for Vertex AI operations, building automated agents for system monitoring, and creating dashboards for efficiency metrics. The role involves collaborating with data science and finance teams to translate efficiency goals into data models and tracking systems, ensuring alignment with budgetary requirements.

This role supports the launch of Generative AI search experiences and education efforts, focusing on responsible AI capabilities. The analyst will perform data analysis to identify and combat abuse, develop datasets and run evaluations for Gen AI products, establish metrics for AI issues, and improve model safety through data analysis. The role requires experience in data analysis, project management, and familiarity with ML model performance or LLMs.

This role focuses on ensuring the security of Google's AI products and features by identifying and mitigating vulnerabilities throughout the product lifecycle. The engineer will analyze AI products, conduct threat modeling, perform research on vulnerabilities, and promote security practices. While leveraging AI tools, the core function is security engineering for AI products, not direct AI model development.

Android Application Engineer for Google Fi Wireless, focusing on scaling the subscriber base, architecting core features, and enhancing functionality using deep Android and telephony expertise. The role involves technical leadership, mentoring junior engineers, and collaborating with cross-functional teams to deliver a seamless user experience. The team leverages Google's AI to solve complex problems and improve customer connectivity.

Software Engineer III, Flume ML at Google, focused on advancing data processing infrastructure, including schedulability and autotuning. The role involves designing and developing data processing features, utilizing AI tools for development, and working with customers on schedulability tests. Requires experience in software development and large-scale infrastructure.

Customer Engineer for Google Cloud's AI Platform, focusing on accelerating AI adoption by providing technical expertise, developing sales assets, and resolving customer blockers in the Japanese market.

Senior Software Engineer to build next-generation, AI-powered infrastructure supporting Continuous Integration (CI) systems for Android, Chrome, and ChromeOS. The role involves designing, implementing, and deploying scalable and reliable systems, with a focus on streamlining operational workflows using Agentic AI and enhancing system reliability. The engineer will also contribute to AI accelerated development and ensure the scalability and availability of infrastructure.

Technical Program Manager III for Google's PLANET team, focusing on networking infrastructure for ML/AI systems (TPUs, GPUs, IPUs). The role involves managing complex, NPI networking programs, defining strategy, and driving cross-functional initiatives to ensure seamless integration and deployment of data center networks that power Google's AI solutions and global services. This is a core infrastructure role supporting AI development and deployment at scale.

Software Engineer role focused on building full-stack web applications and backend services for smart manufacturing, with a key responsibility to integrate AI models (like Gemini) and intelligent agents to enhance factory operations through predictive analysis and anomaly detection. The role involves owning projects from prototype to production and collaborating with cross-functional teams.

This role focuses on enterprise security for AI products, specifically assessing and securing AI agents and features. The engineer will develop threat models, propose guardrails, and advise on mitigating risks associated with AI use, drawing on existing security engineering knowledge and adapting it to the AI context. The role is within the Enterprise Security AI team, contributing to secure AI development and use across the company.

This role focuses on statistical modeling and data analysis for YouTube ads bidding, aiming to improve advertiser success and bidding optimization. It involves building infrastructure, innovating products, and solving performance issues using a mix of engineering, machine learning, and analytical work.

Senior Software Engineer for Google's gUP Eng Support Engagement team, focusing on full-stack development for community platforms. The role involves architecting and building scalable systems, integrating AI/ML models for features like spam classification, and enhancing user engagement and self-service capabilities. Responsibilities include owning the technical roadmap, leading feature development, ensuring system stability and observability, and mentoring other engineers.

Software Engineer II, Enterprise Data Protection at Google, Singapore. This role focuses on building software systems to prevent data exfiltration of intellectual property, including threats from human or autonomous AI agentic actions. The engineer will design, test, deploy, and maintain these security controls across various Google systems. The role requires experience in full-stack development and has a preference for experience in security, machine learning, distributed systems, or AI, specifically agentic software engineering.

This role is for a Software Engineering Manager II at Google, focusing on Emerging On-prem AI Infrastructure in Taipei. The manager will lead a team of engineers, set technical roadmaps for operational tooling and repair automation, and manage systems development engineers. The team's work involves empowering Google customers with AI and Infrastructure at scale, supporting AI model development, and providing platforms for developers. The role requires experience in software development, technical leadership, people management, and building cloud or systems-level infrastructure.

This role is for a Technical Lead in Home Infrastructure at Google, focusing on building and managing scalable serving and offline infrastructure for the Health and Home team. The role involves leading a team, ensuring reliability and low-latency performance of distributed systems, and collaborating with cross-functional teams. While the team uses AI technologies like Gemini, the core responsibility is infrastructure engineering, not direct AI/ML model development.

Senior Software Engineer role focused on developing and managing software for deploying Electronic Design Automation (EDA) tools on Google Cloud. The role involves creating automation, back-end RPC services, and cloud-based solutions for scaling workflows. A key aspect is leveraging advanced machine learning techniques to generate user insights, impacting hardware creation at Google.

This role focuses on the design verification of custom silicon solutions for AI/ML hardware acceleration, specifically Google's Tensor Processing Units (TPUs). The engineer will own the full verification life-cycle, ensuring the reliability and performance of AI/ML workloads on TPU hardware by building constrained-random verification environments and collaborating with design engineers. The role is within the AI and Infrastructure team, which supports Google's AI models and hyperscale computing.

Design Verification Engineer for Google's TPU hardware, focusing on ensuring the reliability and performance of AI/ML workloads on the hardware. This role involves full verification life-cycle management, building verification environments, and collaborating with design engineers to verify complex digital designs for AI/ML acceleration.

Software Engineer III, Full Stack, Cloud AI Developer Tools at Google. This role is part of the AI Developer Tools organization, building client-facing applications that integrate Google's AI capabilities into developer workflows. The engineer will be responsible for the end-to-end delivery of tools like Gemini Code Assist and the Gemini CLI. The role involves designing, writing, and testing code, operating with high agency, transforming ideas into prototypes, and collaborating with Tech Leads and PMs to launch features. The position requires full stack development experience and the use of AI tools in daily workflows.

Senior Software Engineer on the Pixel Audio team, focusing on embedded systems and firmware for earbuds. The role involves designing, developing, and optimizing audio software, with a specific emphasis on architecting features at the interface of voice and Large Language Models (LLMs) within a multi-core, power-constrained environment. Responsibilities include managing performance metrics (MIPS, memory, power) and collaborating with cross-functional teams to deliver features from prototype to launch.

This role focuses on designing and developing optical interconnect technologies for machine learning systems, specifically for TPU and GPU superpods in data centers. The engineer will work on creating next-generation optical transceivers and systems, exploring emerging photonic networking technologies to improve the efficiency of computing systems. While the role supports ML systems, the core craft is in photonic engineering and hardware infrastructure, not direct AI/ML model development.

Google is seeking a Software Engineering Intern to work on AI-integrated software and high-performance applications, focusing on designing, deploying, and maintaining end-to-end infrastructure for large-scale systems. The role involves developing scalable engineering solutions for Google products and applying computer science knowledge to real-world challenges.

Customer Engineer for Google Cloud Platform, focusing on SMB clients in Tokyo. This role involves being the technical expert for sales, designing and implementing custom solutions for partners using Google Cloud. Responsibilities include understanding customer technical needs, advocating for Google Cloud products, prototyping integrations, and recommending architectures. The role requires experience with cloud infrastructure, digital native customers, technical presentations, and familiarity with data and AI, including generative AI and agentic AI solutions.

This role focuses on delivering big data and machine learning solutions to Google Cloud customers, acting as a technical advisor and influencing product roadmaps. It requires experience in building ML/data science solutions and software development.

Software Engineering Manager for database solutions in the semiconductor manufacturing domain, managing a team and overseeing the lifecycle of database applications. The role involves leveraging AI/ML methods like Gemini for technical excellence and productivity improvements.

Senior Software Engineer role focused on developing next-generation storage solutions for AI/ML workloads on Google Cloud Platform. The role involves designing and implementing advanced storage solutions, addressing system design issues, developing production-ready code, and contributing to incubation projects. Responsibilities include writing and testing code, participating in design reviews, reviewing code from peers, triaging and debugging issues, and contributing to documentation. The role requires experience with software development, testing, maintenance, launching products, and software design/architecture, with preferred qualifications in data structures, algorithms, technical leadership, file systems, Linux kernel internals, AI/ML workloads, and cloud computing platforms.

Senior Staff Software Engineer for the Gemini mobile application at Google DeepMind, focusing on delivering new features, driving cross-functional collaboration, and ensuring scalability and performance. The role involves technical leadership and influencing engineering teams within the Gemini ecosystem.

Google is seeking a Software Engineer III to help pivot the Data Engineering Console to an agent-first world, supporting over 22,000 Googlers in managing metascale data flows for various critical applications including Gemini model training, Ads revenue tracking, YouTube video analysis, and Waymo self-driving data. The role involves writing product/system development code, participating in design reviews, reviewing code, contributing to documentation, and triaging/debugging system issues. The ideal candidate will have experience building internal developer tools or AI agent systems.

Senior Software Engineer to advance the schedulability and autotuning capabilities of a planet-scale data processing infrastructure product that powers foundational AI/ML features for YouTube and Search, and next-generation AI initiatives. The role involves designing, developing, and maintaining large-scale software solutions, addressing complex technical challenges, and working with mission-critical customers on schedulability challenges.

Software Engineer role focused on building the software for Google Distributed Cloud (GDC) Connected Identity Verification Service (IDVS). The role involves designing and implementing components for a rack designer validation suite, including rack design, elevations, BOMs, cables, and devices. It also requires building data pipelines for AIOps to enable automated decision-making using system telemetry, and participating in on-call rotations for production issue resolution. The role emphasizes partnering with other engineering teams to improve global infrastructure reliability and problem-solving.

This role focuses on identifying and combating egregious online harms across Google products by leveraging technical acumen and data analysis. The analyst will partner with Product, Engineering, Policy, and Legal teams to design and develop solutions for detecting and enforcing against abuse. Key responsibilities include performing data analyses, identifying improvements for detection and enforcement systems, leading projects, and analyzing the performance of technical models like ML systems and LLMs.

Senior Software Engineer role focused on systems performance for AR/VR glasses, involving optimization, power saving, and defining quality metrics. The role touches on AI/ML for perception models and the convergence of AI and XR, but the core craft is systems performance engineering.

Google is seeking an Engineering Manager for Search Platforms in Bengaluru, India. This role involves technical leadership, team management, and contributing to product strategy for large-scale projects in areas like information retrieval, AI, and NLP. The manager will set team priorities, develop roadmaps, guide system designs, and oversee code reviews, focusing on optimizing user-visible search latency and ensuring performant, reliable execution of search products.

Software Engineer III for Google Cloud's BigQuery, focusing on enabling data science, data engineering, and AI/ML workflows at scale. The role involves feature design, development, deployment, monitoring, and customer support for BigQuery's capabilities, including running LLMs and creating ML models on large datasets.