This role focuses on designing and developing next-generation networking infrastructure for large-scale AI training and inference in Azure Cloud. The engineer will work on high-performance, low-latency, and low-jitter communication frameworks, optimizing scalability and reliability for distributed AI workloads.

Principal Software Engineer role focused on designing, developing, and optimizing networking infrastructure for large-scale AI training and inference in Azure Cloud. The role emphasizes high performance, low latency, and reliability for distributed AI workloads, working with AI accelerators and advanced networking technologies.

The role focuses on designing and building cutting-edge networking infrastructure for large-scale AI training and inference in Azure Cloud. The goal is to enable breakthroughs in AI by delivering unmatched computational power, scalability, and reliability, with a focus on high performance, low latency, and minimal jitter for distributed AI workloads.

This role focuses on building and operating the core platform infrastructure for training, evaluating, and deploying large-scale AI models within Microsoft. It involves designing scalable services for cluster orchestration, job scheduling, data pipelines, and artifact management, with a strong emphasis on production operations, cloud platforms (Azure), and enhancing developer experience for AI research and engineering teams.

This role is focused on ensuring the reliability, performance, and availability of Microsoft's large-scale AI training infrastructures, which involve tens of thousands of GPUs and advanced networking. The responsibilities include designing transport, fabric architecture, telemetry, observability, and automated troubleshooting for these clusters. The role also involves AI training and inference cluster bring-up, performance benchmarking, and root-cause analysis, with a goal of developing predictive health models and autonomous remediation systems.

Technical Program Manager for AI Infrastructure at Microsoft AI, focusing on building and optimizing platforms for large-scale foundation model training, deployment, and serving. The role involves coordinating projects, collaborating with researchers and engineers, and driving progress in a 0->1 environment.