Microsoft has 521 active AI-related job listings. The majority of these roles are focused on agents, representing 37% of the total, followed by application and serving infrastructure. Engineering is the most frequent function, with a significant number of openings, and the United States is the primary hiring country. Frequent tech tags include agent orchestration, model serving, and LLM observability, suggesting a focus on operationalizing AI models. Over the last 30 days, Microsoft has added 280 new AI roles, a 157% increase compared to the previous 30-day period.
Currently tracking 250 active AI roles, down 24% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$331k (avg $195k).
Microsoft currently has 343 active AI-related roles in our index. The most common open titles are: Principal Software Engineer (19), Senior Software Engineer (19), Software Engineer II (8), Principal Applied Scientist (7), Principal Data Scientist (4). Most positions are in Engineering and Research.
Microsoft's active AI hiring is concentrated in: agents (36%), application (21%), serving infrastructure (19%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Microsoft is hiring AI talent in: United States (308 roles), Canada (15 roles), Japan (8 roles), United Kingdom (7 roles).
Job postings at Microsoft most frequently mention: Computer Architecture, Python, Machine Learning, C#, C++.
In the past 30 days, Microsoft has posted 227 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Senior Researcher: Machine Learning Senior Researcher focused on foundational machine learning research, emphasizing efficiency, intelligence, and alignment, with a strong publication record and collaboration across disciplines. The role involves spearheading research initiatives, translating theoretical concepts into tangible solutions, and mentoring interns. | Pretrain | 9 |
| Cambridge Residency Programme - Researcher in Agentic AI Systems & Infrastructure Researcher in Agentic AI Systems & Infrastructure focusing on multiagent system designs, memory, communication, and orchestration using ML and systems techniques. Prototyping components for multiagent inference with system-level optimizations and exploring ML & systems codesign. Evaluating ideas through experiments and benchmarks. | Agent |
| 9 |
| AI for Science Residency - Machine Learning Resident Research scientist role focused on developing machine learning models for materials science, including generative models and potentially agent-driven research, with a strong emphasis on publications and interdisciplinary collaboration. | Post-trainData | 9 |
| Cambridge Residency Programme - Postdoc Researcher, Generative Experiences & Collaborative Workflows Researcher for People-Centric AI at Microsoft Research Cambridge focusing on developing tools that use generative AI to create dynamic user experiences, co-created with user input, particularly for activity-centric and collaborative scenarios. The role involves blending research disciplines, design, and engineering to shape human-AI interaction. | AgentPost-train | 9 |
| Research Science PhD Internship Opportunities - Coding Agents Research internship focused on advancing coding agents that can understand codebases and autonomously execute software engineering tasks. This involves building LLM-based agents for feature implementation and bug fixing, enhancing their ability to plan and use developer tools, and improving reliability through feedback. | Agent | 9 |
| Research Intern - AI Agents & Efficiency Research intern role focused on building advanced LLM agents with memory, tool use, and multi-agent collaboration, and driving efficiency in LLM applications through context engineering, adaptive inference, and system optimization. | AgentServe | 9 |
| Member of Technical Staff, High Performance Computing Engineer - MAI SuperIntelligence Team This role focuses on building and scaling the high-performance computing (HPC) infrastructure required for training frontier AI models and powering AI products like Copilot. The engineer will design, operate, and maintain large-scale HPC environments, including schedulers and core domains like GPU compute, storage, and networking. Responsibilities include developing automation tools, supporting researchers and engineers, and troubleshooting cluster issues to ensure efficient job scheduling and performance. | Pretrain | 9 |
| Member of Technical Staff -Member of Technical Staff - Pretraining Text Data Seeking engineers and researchers to join the Pretraining Text Data team to build the next generation of foundation large language models. The role focuses on designing and curating high-quality datasets, developing novel data collection strategies, improving dataset quality and integrity, understanding data-driven model behaviors, training models on data impact, and aligning datasets with ethical and societal values. This is a cross-disciplinary, high-impact role at the intersection of data and innovation. | Data | 9 |
| Member of Technical Staff, Software Co-Design AI HPC Systems - MAI Superintelligence Team This role focuses on the co-design and productionization of next-generation AI systems at datacenter scale, optimizing performance, efficiency, and cost across hardware and software. It involves analyzing workloads, driving architectural decisions, optimizing distributed systems for training and inference, and influencing AI hardware design. The role also includes performance modeling, prototyping, and mentoring. | ServePretrain | 9 |
| Member of Technical Staff - AI Pretraining - MAI Superintelligence Team Microsoft AI is seeking individuals to train the world's most capable AI frontier models, focusing on scale, performance, and product deployment. The role involves developing algorithms, model architectures, and data mixtures for large-scale training, driving implementations, conducting experiments, and collaborating with infrastructure, data, post-training, and multimodality teams. | Pretrain | 9 |
| Member of Technical Staff, AI Multimodal - MAI Superintelligence Team Research role focused on training frontier multimodal AI foundation models at scale, pushing boundaries of performance and deployment. Involves algorithm development, model architecture design, experimentation, data innovation, and improving training/deployment efficiency. | Pretrain | 9 |
| Member of Technical Staff, AI Post-Training - MAI Superintelligence Team Post-Training - Develops and ships post-training methods for large language models (LLMs) used in Microsoft Copilot, focusing on data collection, evaluation, finetuning algorithms, and prototyping new capabilities. Collaborates with pretraining and product platform teams to deploy models and improve them based on user feedback. | Post-train | 9 |
| Member of Technical Staff, AI Data - MAI Superintelligence Team The AI Data team at Microsoft AI is building the world's most advanced multimodal dataset to power frontier AI models. This role focuses on designing and developing data pipelines for massive multi-modal training data (text, audio, images, video) and building infrastructure to store and process petabytes of data. The team partners with pre-training and post-training teams to improve data recipes through experimentation and collaborates with product teams to identify model gaps. | DataPretrain | 9 |
| Senior Applied Scientist Senior Applied Scientist focused on retrieval technologies for Microsoft 365 Copilot, specifically Search, Chat, and Agent experiences. The role involves designing, experimenting with, and evaluating retrieval and ranking systems, including semantic, dense, sparse, and hybrid retrieval, RAG, and LLM-integrated architectures, to enhance grounding, relevance, and reasoning for millions of enterprise users. | AgentServe | 8 |
| Cambridge Residency Programme: Next-Generation AI Datacentre Networking Microsoft Research Cambridge is seeking two researchers for a two-year postdoctoral program to advance the design and evaluation of next-generation datacentre networks specifically for AI training and inference workloads. The program involves two tracks: one focused on analytical modeling and simulation, and the other on systems implementation and experimental validation using advanced hardware testbeds. The goal is to publish research findings and influence future AI infrastructure strategy. | Serve | 8 |
| AI for Science Postdoctoral Researcher - Biomolecular AI & Experimental Data Integration Postdoctoral Researcher focused on integrating experimental biological data with machine learning models for biomolecular simulation and drug discovery. The role involves designing and scaling experimental datasets, developing methods to connect ML models with experimental observables, and creating closed-loop workflows between models and experiments. | Data | 8 |
| Principal Product Designer, AI Experiences Product Designer for Microsoft's Superintelligence Team, focusing on end-to-end UX for AI product surfaces like MM Labs and Playground. This role leverages AI-native tools and agentic coding workflows to rapidly prototype and ship UI, bridging the gap between design and engineering. The designer will collaborate with researchers and model designers, contribute to design systems, and use data to inform decisions, with a high bar for visual craft and interaction quality. | Ship | 8 |
| Member of Technical Staff, AI Networking - MAI Superintelligence Team This role focuses on designing, scaling, and optimizing high-performance networks for AI training and inference clusters. The engineer will work on the end-to-end networking architecture, from link-layer to fabric-wide systems, connecting thousands of GPUs. Responsibilities include benchmarking, profiling, debugging, and tuning AI workloads, engineering ultra-low-latency networks, and designing congestion-free transport mechanisms. The goal is to build networking systems that directly accelerate Microsoft's frontier AI models and support the development of advanced AI systems. | Serve | 8 |
| Senior Software Engineer Senior Software Engineer role focused on designing and delivering AI/ML/LLM-based solutions for enterprise customers, involving prompt engineering, RAG, deployment, operation, evaluation, and monitoring of AI systems using cloud platforms. | Agent | 7 |
| Principal Technical Program Management Specialist This role translates early-stage AI research from Microsoft Research and applied R&D into shippable cloud AI capabilities. The Principal Technical Program Manager will shape technical concepts into product roadmaps, drive execution with Azure engineering teams, and manage external suppliers. The role involves defining success criteria, technical bars, and launch criteria for moving research prototypes to general availability, and managing program structure, roadmap, schedule, and governance for multi-team efforts. It also involves closing the loop from production back to research by validating use cases and bringing customer feedback to shape future investments. | Ship | 7 |
| Senior Data Scientist - Industry Solutions Engineering Senior Data Scientist role focused on co-engineering AI-powered, cloud-based solutions with customers to solve complex business challenges. The role involves data acquisition, preparation, model development, evaluation, and deployment within a cross-functional team, contributing to reusable solution patterns. | Ship | 7 |
| Forward Deployed Engineer Forward Deployed Engineer (FDE) role focused on building and deploying AI-powered solutions for customers, working at the intersection of advanced AI technology and real-world business impact. Responsibilities include engineering data pipelines, building custom applications, deploying scalable workflows, and monitoring/refining solutions. Requires practical experience with AI/LLMs in production and leveraging generative AI. | AgentServe | 7 |
| Member of Technical Staff, Hardware Health - MAI Superintelligence Team 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. | Serve | 7 |
| Member of Technical Staff, Data Research Engineer - MAI Superintelligence Team Seeking Data Research Engineers to join the Multimodal team, focusing on building next-generation foundation models. The role involves exploring, designing, and building high-quality multimodal datasets (vision, language, audio) for training and evaluation, collaborating with scientists and engineers, and developing scalable data pipelines. Responsibilities include data analysis, quality assessment, building tools for auditing, and ensuring datasets meet responsible AI practices. | Data | 7 |