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.

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.

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.

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.

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.

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.

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.