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, 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 |
| 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 |
| 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 |