This role focuses on building and iterating on Responsible AI tools and capabilities to enable developers to build and deploy AI responsibly at scale. It involves prototyping, applying subject-matter expertise, and collaborating across product groups to drive project and release plans. The role emphasizes working in fast-paced, experimental environments and taking ideas from ambiguity to production.

Principal Data Scientist at Microsoft responsible for end-to-end delivery of strategic data science projects, partnering with customers and internal teams to design and implement advanced analytics and AI solutions that create measurable business impact. This role involves leading teams, engaging with stakeholders, applying machine learning, and integrating data models into customer systems, with a focus on Responsible AI principles.

Software Engineers (II and Senior) needed to lead engineering efforts for Teams Copilot, leveraging Generative AI, LLMs, and an AI stack to enhance collaboration and user experience. The role involves end-to-end ownership, prototyping, evaluating new AI features, and developing scalable, reliable services with a focus on live-site operations and data-driven decisions.

This role focuses on building cross-cutting capabilities for AI companions like Copilot, spanning multiple modalities (text, voice, vision, action). The engineer will own features end-to-end, collaborate with AI researchers, and ship experiments rapidly to create user experiences that redefine AI companionship. The role requires strong full-stack fundamentals and comfort with ambiguity in a fast-paced environment.

This role focuses on building and architecting distributed data platforms and pipelines that process massive datasets for AI models, including training, inference, and evaluation. It involves designing event-driven architectures, handling unstructured data, engineering feedback loops for AI, and optimizing compute for cost and performance.

Backend Engineer role focused on building the data foundations for Copilot's memory and personalization features. This involves designing and operating large-scale data pipelines for signal ingestion, normalization, enrichment, aggregation, and memory generation, enabling downstream ML and product consumers. The role also involves technical leadership in data systems and influencing architecture.

Software Engineer role focused on building and scaling the inferencing cloud for Large Language Models and GenAI Services within Azure CoreAI Platform. The role involves designing, building, and operating large-scale engineering systems for AI models.

Senior Software Engineer role focused on designing, developing, and optimizing Azure's High Performance Computing and AI Platform (HPC/AI) virtual machines. This involves deep technical work on hardware/software interactions, device virtualization, and performance analysis of GPU workloads for large-scale AI training and inference. The role contributes to the underlying platform software and its exposure as an Azure service, with opportunities to work on upper layers of Azure infrastructure.

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.

Engineering Lead to build and own the software engineering platform for large-scale machine learning retrieval systems, including RAG for Copilots, web-scale search, and personalized recommendations. The role focuses on translating retrieval research into reusable, scalable systems, defining engineering standards, and integrating new methods. It involves cross-team technical leadership and improving developer/researcher experience.

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.

The AI Data Infra team at Microsoft AI is responsible for building data infrastructure to help MAI teams to generate the biggest and best training dataset. This role focuses on designing and developing data pipelines for multimodal training data and owning critical data infrastructures like Spark, Ray, and Vector Databases.

Senior/Principal Security Researcher on the Global Hunting, Oversight, and Strategic Triage (GHOST) team. The role involves performing threat hunts, assisting with investigations, developing threat intelligence, and cultivating investigation best practices into Microsoft tooling and products. Researchers will support a global team to identify and catalog new attacker TTPs, victims, and deliver customer notifications to protect worldwide enterprise customers and empower customers to protect themselves via constantly improving Microsoft products.

Software Engineer on the Path team at Microsoft, focusing on modernizing work management products (Project, Planner, To Do, Visio) with AI. The role involves pioneering LLMs and agentic frameworks to automate tasks and streamline workflows, contributing to the development of AI-powered productivity tools.

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.

Senior Software Engineer to build GitHub's coding agent CLI and the core agent loop powering agentic experiences across GitHub and Microsoft. The role focuses on turning AI systems into reliable developer tools, with an emphasis on agentic systems, tool design, agent loops, benchmarking, quality optimization, and high-performance terminal experiences.

This role focuses on building large-scale Copilot memory and personalization systems using RAG, search, embeddings, retrieval, and ranking. The individual will be responsible for designing and implementing these systems, collaborating with stakeholders, and mentoring engineers. Experience with LLM applications and large-scale embedding/retrieval/ranking systems is required.

Engineering Manager for Copilot Memory and Personalization, focusing on building AI systems that remember, evolve, and personalize user experiences. The role involves leading a team of backend and ML engineers, contributing to codebase and infrastructure, and shipping AI-powered features for millions of users.

Software Engineer II role focused on designing and building AI-powered scheduling systems by integrating backend services, LLMs, APIs, and Outlook services for Microsoft Calendar and Teams. The role involves developing agent-driven solutions to reduce cognitive load and empower users in the hybrid work era.

This role focuses on engineering user-facing AI features for Microsoft's personal AI, Copilot. The engineer will own the development lifecycle from inception to delivery, build secure and performant AI platform services, and collaborate with researchers and other engineers to create next-generation AI products. The role emphasizes shipping high-quality, well-tested, secure, and maintainable code within a fast-paced product development cycle.

This role focuses on building AI-powered web experiences for Microsoft Copilot, collaborating with researchers and product managers to deliver a world-class AI companion. The engineer will design and build efficient front-end systems and infrastructure for complex web applications, ensuring safety and reliability for millions of users.

Lead a team of software engineers to develop and launch AI-powered features for educational technology products, focusing on consumer-facing applications like study modes and quiz generation. This role involves people management, technical leadership, and collaboration with cross-functional teams to deliver impactful AI solutions in the EdTech domain.

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.

The role focuses on building and maintaining data infrastructure for large-scale AI model training, specifically ingesting and processing enormous amounts of multimodal data (text, audio, images, video). This includes owning data pipelines, Spark, Ray, and Vector Databases, and partnering with pretraining and post-training teams to improve the data recipe for frontier models.

The Microsoft 365 Copilot Windows App team is building intelligent, multimodal AI experiences into Windows, enabling AI agents using MCP to redefine user interaction with devices and bring AI to billions. The role involves designing and implementing intelligent features leveraging voice, camera, and screen context, building and optimizing agentic workflows, and owning end-to-end AI capabilities.

Software Engineer II - CoreAI role focused on developing connectors and enriching ingested content with AI/ML capabilities for Azure AI Search, aiming to make it the knowledge and memory layer for Agentic applications. This involves generating vector embeddings, transforming data, and advancing multi-modal search.