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 strategic partnerships for acquiring third-party data to power foundational AI models like Gemini. The responsibilities include understanding AI research needs, identifying and evaluating data partners (especially in the media sector), negotiating agreements, and managing relationships to ensure a pipeline of data assets aligned with AI model priorities.

This role focuses on strategic sourcing and negotiation of third-party data partnerships to power foundational AI models like Gemini. The manager will translate research needs into data acquisition strategies, build and manage a pipeline of data assets, and lead negotiations for partnership agreements, ensuring alignment with AI model development priorities.

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.

This role is for a Software Engineering Manager leading the Continuous Integration and Release (CI&R) team within the Git ecosystem at Google. The team is responsible for CI/CD and artifact management infrastructure, aiming to transform how Google engineers develop software. The manager will set strategy, lead a team, and drive technical direction, with a focus on CI/CD, Git, software supply chain security, and infusing AI/ML to enhance developer velocity and product quality.

Staff Software Engineer role focused on building and scaling compute infrastructure solutions for Google Cloud, specifically for AI/ML workloads, virtual machines, and bare metal solutions. The role involves innovating in virtualized storage, networking, and workload management to ensure the availability, reliability, and performance of infrastructure powering VM instances.

Software Engineer role focused on building and launching high-quality features for large applications, specifically within Google Cloud's database observability service. The role involves full-stack development, partnering with product and design teams, and influencing product direction. While the product offers AI-driven experiences and the role involves integrating AI technologies, the core craft is not AI/ML model development.

This role focuses on growing Google's AI business by building and expanding customer relationships, demonstrating product functionality, and identifying business use cases. The AI Sales Specialist will work with customers to deliver business value and help them build new products leveraging Google's AI solutions, while also managing day-to-day relationships with cross-functional teams and external customers.

This role is a Solutions Consultant for Google for Education, focusing on integrating Google's tools, including AI-powered ones like Gemini, into educational institutions. The role involves direct sales, technical advocacy, customer requirement analysis, solution design, and presenting product demonstrations. While AI tools are used and promoted, the core function is not building or researching AI models but rather applying them within an educational product context.

This role focuses on the verification of AI/ML hardware accelerators (TPUs) that power Google's AI/ML applications. The engineer will ensure the reliability and performance of these complex digital designs by developing verification environments, writing tests, and collaborating with design teams throughout the full verification lifecycle.

Staff Software Engineer at Google Cloud's GCE team, focusing on building and scaling compute infrastructure for AI/ML workloads. The role involves innovating in virtualized storage, networking, and customer workload management to support training and inference VMs, ensuring availability, reliability, and performance of the underlying infrastructure.

This role involves developing custom silicon solutions (ASICs) for accelerating machine learning computation in data centers. The engineer will collaborate on micro-architecture, design, and integration of these accelerators, focusing on performance, power, and area. While the role is in hardware engineering, it directly supports AI/ML infrastructure.

This role is a Quality Control Manager for Google's gTech Ads division, focusing on improving customer experience and operational efficiency within the advertising products stack. The manager will establish quality processes, leverage automation and ML for quality control, share insights, and drive standardization across regions. While the role mentions utilizing ML and AI tools, its core function is quality management and process improvement within an advertising support context, not direct AI/ML model development or research.

Software Engineer role focused on Cloud Infrastructure Engineering, specifically on delivering efficient compute solutions for Google Cloud. The role involves optimizing resource usage, collaborating with data science teams on statistical modeling for capacity planning, integrating resource management tools, and developing new cluster management products. The work impacts both ML and non-ML use cases, aiming to improve compute and ML resource efficiency for financial and environmental benefits.

This role focuses on using and improving Large Language Models (LLMs) for content moderation and anti-abuse efforts on YouTube. Responsibilities include designing and refining prompts for LLMs, analyzing data to understand abuse impact, and driving experiments to prevent abuse. The role involves working with data, identifying product vulnerabilities, and collaborating with engineers and stakeholders.

Software Engineer focused on AI security within Google Cloud, responsible for designing and developing security services for AI, collaborating on productization, ensuring service availability, and mentoring team members. Requires 5 years of software development experience and 3 years of experience with software products, design, and architecture.

This role focuses on managing and mitigating payment fraud and abuse for Google products, investigating incidents, performing statistical analysis, and collaborating with engineering teams to enhance tools and systems. It involves assessing product risk, designing mitigation strategies, and working with cross-functional teams to launch solutions. While it uses ML systems and has preferred qualifications in ML/LLMs, the core function is risk management and fraud prevention, not direct AI model development.

This role is for a Silicon Validation Lead focused on AI/ML hardware acceleration, specifically Tensor Processing Units (TPUs). The lead will manage a team responsible for the post-silicon validation of AI/ML SoCs, ensuring timely bring-up, enablement, and debug. The role involves close collaboration with various engineering teams (architecture, design, verification, firmware, software, platform) and people management responsibilities.

This is a PhD intern role focused on developing and maintaining the end-to-end infrastructure for AI-integrated software and large-scale systems at Google. The intern will work on complex computer science solutions and scalable, distributed software systems.

Product Manager for Google Cloud's AlloyDB for PostgreSQL portfolio, focusing on driving AI product strategy and roadmaps, engaging with customers, and partnering with engineering and research teams to launch and improve database services.

Staff Software Engineer at Google Cloud focused on optimizing fleet transformation and operations using ML-powered simulations and discrete algorithms. The role involves migrating from MIP models to ML for predictive, self-governing systems, designing simulation engines, and guiding automated policy enforcement for AI/ML compute needs.

This role is for a PhD Software Engineer focused on Fleet Analytics within Google Cloud's AI and Infrastructure organization. The role involves designing, developing, and maintaining software solutions, with a focus on advanced optimization models. While the organization works with AI/ML systems, this specific role's primary output is optimization models and platform capabilities, not direct AI/ML model development or deployment.

This role focuses on the verification of AI/ML hardware accelerators (TPUs) for Google Cloud. The engineer will be responsible for the full verification life-cycle, ensuring the reliability and performance of AI/ML workloads on TPU hardware. This involves creating verification environments, identifying coverage measures, debugging, and collaborating with design engineers. While the role is deeply involved with AI/ML hardware, the core craft is hardware verification engineering, not AI/ML model development or research.

Engineering Manager for Google Home Growth, focusing on hardware, software, and AI to grow the subscription business. Responsibilities include setting team priorities, managing engineers, developing technical roadmaps, guiding system designs, and reviewing code. Requires experience in software development, Android development, and technical/people management.

Senior Product Manager for Google Cloud's AlloyDB for PostgreSQL portfolio, focusing on driving product strategy, roadmap, and integration with AI capabilities within the database and broader Google Cloud ecosystem. This role involves customer engagement, cross-functional collaboration with engineering and research, and defining data-driven metrics to improve developer experience.

Google is seeking a Software Engineering Manager for their Switch Infrastructure team in Bengaluru, India. This role involves leading and mentoring a team of engineers responsible for the testing and validation of Google's network switch hardware and software. The team's work is critical for supporting all major Google services, including AI/ML infrastructure like Gemini, and focuses on advancing network infrastructure for scalability, agility, reliability, and innovation. The manager will define strategy, drive execution, collaborate with cross-functional teams, and foster a culture of engineering excellence. Minimum qualifications include a Bachelor's degree, 8 years of software engineering/test automation/network engineering experience, experience with Ethernet switches, C++/Python development, team leadership, and data center networking.

This role is a Policy Enforcement Manager for YouTube's Partner Program, focusing on strategy, operationalizing scalable policies, and mitigating brand risk. It involves working with cross-functional teams, reviewing sensitive content, and utilizing GenAI tools for abuse mitigation and enforcement. The role requires experience with LLMs in operations and SQL.

Staff Software Engineer for Google Distributed Cloud Hosted (GDCag), focusing on building a scalable platform for air-gapped environments. The role involves defining and implementing Agentic AI opportunities for fault remediation, influencing security architecture, and collaborating with various teams to deliver the GDCag software stack. Requires extensive experience in software development, large-scale infrastructure, distributed systems, and cloud environments, with a focus on security and operational efficiency.

Product Data Scientist role focused on optimizing Google's Payments products and solutions, specifically the Smart Router infrastructure which uses ML/AI for transaction processing. The role involves driving analytics for FOP optimization, influencing strategy, and collaborating with product and engineering teams to improve buyflows and conversion rates on platforms like Play and YouTube.

This role focuses on identifying and addressing threats against Google Ads accounts, specifically in hijacking and scaled abuse. The analyst will use investigative, technical, and security skills to solve complex problems at scale, working closely with Engineering and Product teams to adapt defenses against new threat vectors. Responsibilities include delivering insights into account takeover threats, developing early warning alerts, leading incident responses, and collaborating with vendors to scale protection. The role also involves building, leveraging, and evaluating models and operations to combat cyber security and abuse issues.

Software Engineer III, Full Stack role within Google Cloud's AI and Infrastructure team, focusing on building and enhancing large-scale AI and infrastructure solutions that empower Google customers and users worldwide. The role involves full-stack development, managing project priorities, and contributing to the innovation of hyperscale computing technologies.

Staff Software Engineer role at Google Cloud, focusing on AI and Infrastructure. The role involves providing technical leadership, managing projects, and designing/developing large-scale software solutions that support Google's AI models and infrastructure. While the team works with AI, the core responsibilities are in software engineering and infrastructure, not direct AI/ML model development.

This role focuses on applying advanced statistical methods, particularly causal inference and differential privacy, to design experiments, assess attribution, and develop privacy-preserving marketing products within Google's advertising ecosystem. The lead will translate these methodologies into deployed products, provide technical guidance, and shape global strategies. While ML is mentioned as a preferred qualification, the core focus is on statistical analysis and causal inference for measurement and product development, not core AI/ML model building.

This role focuses on building and implementing ML networking infrastructure for Google Cloud, specifically enhancing GPU-to-GPU communication and enabling ML workloads. While it supports ML, the core craft is in networking infrastructure and engineering, not direct AI/ML model development.

Google is seeking a PhD Software Engineer for their AI and Infrastructure (AI2) organization in Bengaluru. This role focuses on developing next-generation storage architectures, backup, and replication solutions. The engineer will drive research initiatives, improve system reliability and performance, and collaborate with stakeholders. The position requires a PhD in a related technical field and experience in data storage, distributed systems, and research publication. While the role is within an AI/ML-focused organization, the core responsibilities are in data storage and distributed systems engineering, not direct AI model development.

Google is seeking a Senior Software Engineer for its Google Cloud division. The role involves developing and enhancing software solutions, managing project priorities, and contributing to the full software development lifecycle. The engineer will work on critical projects, potentially across various technology areas including AI and NLP, and will be responsible for writing and testing code, participating in design reviews, and debugging issues.

Software Engineer role at Google Payments, focusing on developing and enhancing software solutions for payment technologies. The role involves coding, design reviews, code reviews, documentation, and issue triaging. It requires a Bachelor's degree and 2 years of software development experience.

This role is for a Senior Software Engineer at Google's Corp Eng team, focusing on building world-leading business solutions for internal Google use. The engineer will be responsible for the full software development lifecycle, including design, development, testing, deployment, maintenance, and enhancement of software solutions. The role requires strong software development experience, including design, architecture, and testing, with a focus on scalability and efficiency. While AI/ML is mentioned as a potential area of interest for Google's products, this specific role within Corp Eng is centered on building internal business solutions and IT infrastructure, not directly on shipping AI/ML models or agents.

Google's Consumer Hardware Silicon division is seeking Silicon Engineers to design, develop, and deploy consumer hardware, including chips optimized for machine learning, imaging, video, and security. The role involves working on ASIC/SoC design, verification, and implementation, collaborating with cross-functional teams in a fast-paced, product-oriented environment.

Software Engineer III, Mobile at Google, focusing on developing and enhancing software solutions for the Payments team. Responsibilities include writing code, leading design reviews, reviewing code, contributing to documentation, and triaging/debugging issues. Requires a Bachelor's degree and software development experience.

Software Engineer III for the YouTube Live team in Bangalore, focusing on modernizing the living room experience and building a scalable creator platform. Responsibilities include writing product/system code, participating in design reviews, code reviews, contributing to documentation, and triaging/debugging issues.

Software Engineering Manager for Graph Intelligence, Core at Google in Bengaluru. This role involves technical leadership, people management, setting team priorities, developing roadmaps, designing systems, and reviewing code. The focus is on building the technical foundation behind Google's flagship products, including areas like information retrieval, artificial intelligence, natural language processing, and large-scale system design. The role requires experience in software development and technical/people management.

Embedded Software Engineer role at Google, focusing on developing device drivers and system architecture for next-generation smart devices. Requires experience in embedded systems, C/C++, and Linux/RTOS.

This role is for a Silicon Design Verification Engineer focused on digital design blocks and verification environments using SystemVerilog and UVM. The role involves planning verification, creating testbenches, identifying coverage, debugging, and measuring coverage to ensure functionally correct design blocks. While the team works on AI/ML accelerators and TPUs, the core function of this role is hardware verification, not direct AI/ML model development.

Develops custom silicon solutions (ASICs) for accelerating machine learning computation in data centers, collaborating with various engineering teams on microarchitecture, implementation, and optimization for performance, power, and area.

Software Engineer III role at Google Cloud, focusing on developing and enhancing software solutions for cloud products. The role involves managing project priorities, designing, developing, testing, deploying, and maintaining software. While AI/ML is mentioned as a technology area within Google Cloud, the core responsibilities are general software engineering for cloud services, not direct AI/ML model development or research.

Product Manager role focused on user-generated content and content trust within Google's Geo products. The role involves defining product strategy, leading cross-functional teams, and working with ML/Platform teams to deliver user-centric experiences. Requires extensive product management and technical leadership experience.