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 |
|---|---|---|
| Research Intern - AI Frontiers Research Intern position at Microsoft AI Frontiers Lab focusing on advancing agentic model capabilities. The role involves creating models and agents that can perform tasks across digital systems using automation, reasoning, and interaction, leveraging both text and visual environments. The research includes areas like reinforcement learning for reasoning and tool use, novel training algorithms, synthetic environment creation, multi-agent training, scaling laws, and optimization techniques. The role also involves working with various data modalities and modern model architectures, with a focus on publishing in top-tier venues and potentially shipping AI technologies in products. | AgentPost-train | 10 |
| Senior Researcher - Artificial Intelligence and Machine Learning - Microsoft Research Senior Researcher in AI/ML at Microsoft Research New England, focusing on defining and driving an independent research agenda in theoretical and applied AI/ML. Requires a PhD and a strong publication record at top venues. |
| Pretrain |
| 10 |
| Researcher Researcher at Microsoft Research India focusing on advancing innovation in AI/ML, including new models, scalable ML architectures, systems support, and large-scale applications. The role involves tackling open research problems, collaborating with teams, and driving research towards impactful publications and industry trends. | Pretrain | 10 |
| Senior Researcher - Foundations of Generative AI- Microsoft Research Senior Researcher focused on the foundations of generative AI, including new architectures, representations, and learning objectives for foundation models and learning agent platforms. Research areas include proactive agents, test time training, active visual reasoning, world models, multi-scale temporal reasoning, continual learning, multimodal models (VLM, VLA), and real-time agents. | PretrainAgent | 10 |
| Research Intern - MSR Montreal / ML Team Research Intern position at Microsoft Research Montreal focusing on advancing LLM research in reasoning, interaction (RL training), and modularity, specifically for agentic coding LLMs. The role involves developing, improving, and exploring AI model capabilities, contributing to cutting-edge technologies, and potentially publishing research. | PretrainPost-train | 10 |
| 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 |
| Research Fellow Microsoft Research India is seeking Research Fellows for a 1-2 year program. The role involves pushing the frontiers of computer science and technology, with a focus on developing core ML/optimization/cryptography algorithms, large-scale retrieval models, reliable reasoning with LLMs, LLM inclusivity, and AI training/inference infrastructure. The goal is to create academic, industry, and societal impact. | PretrainServe | 9 |
| Applied Scientist- II Applied Scientist II role focused on fine-tuning frontier LLMs for enterprise data, enabling task-specific agents and solutions. The role involves research in LLM post-training, particularly reinforcement learning for long-horizon dynamic workflows, and driving research into product capabilities for M365 Copilot. | Post-trainAgent | 9 |
| Senior Researcher - Efficient AI Applied research role focused on advancing efficiency across the AI stack for large-scale generative AI experiences in Microsoft 365. The role involves optimizing AI serving systems from algorithmic and systems levels down to hardware and kernel optimizations, with a focus on end-to-end ownership from research to production deployment. | Serve | 9 |
| Researcher Intern Applied Researcher Intern role focusing on AI for developers, specifically post-training code-specific models and agentic research for tools like Github Copilot. The role involves building and training state-of-the-art models, applying LLMs to software engineering tasks, and running large-scale experiments. | Post-trainAgent | 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. | AgentServe | 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 |
| AI for Science Internship - Machine Learning Intern AI for Science Internship - Machine Learning Intern at Microsoft Research AI for Science, focusing on developing next-generation foundational AI capabilities for materials design. The role involves contributing to research on efficient and expressive ML models, working with domain experts, and preparing technical papers. Experience with generative models and agent-driven research is preferred. | Post-trainAgent | 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 Sciences INTERN Research intern position at Microsoft focusing on analyzing and improving advanced algorithms in machine intelligence and machine learning applications, implementing scalable AI system prototypes, and developing solutions for large-scale, real-world problems. Requires strong academic experience and potentially publication history. | Pretrain | 9 |
| Principal Applied Researcher Principal Applied Researcher to lead research projects on AI for developers, taking them from research into product. This role involves collaborating with scientists, engineers, and designers, building and training state-of-the-art models, applying and advancing LLMs for software engineering (including RAG and evaluation), and running experiments on a large scale with developer product teams. | ShipPost-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 - Self-Improving AI Research Intern position focused on self-improving AI systems, involving language modeling and reinforcement learning. The role is part of Microsoft Research NYC and requires enrollment in a PhD or master's program with experience in deep learning, language modeling, and/or reinforcement learning. Preferred qualifications include experience with deep learning frameworks like PyTorch and Hugging Face Transformers. | Post-trainAgent | 9 |
| Research Science: Internship opportunities This is an internship opportunity for a Research Scientist at Microsoft, focusing on advancing the state-of-the-art in computer science and engineering through research in areas like Machine Learning, Natural Language Understanding, and Computer Vision. The role involves conducting research, implementing prototypes, and collaborating with teams to push forward research agendas, with a strong emphasis on academic experience and deep thinking. | Pretrain | 9 |
| Principal Researcher Applied research role focused on advancing efficiency across the AI stack (models, ML frameworks, cloud infrastructure, hardware) for generative AI serving systems. The role involves exploring algorithmic, systems, and hardware/software co-design techniques for optimizations like batching, routing, scheduling, caching, and GPU architecture-aware optimizations. Emphasis on end-to-end ownership, driving research through prototyping, validation, and deployment to production for measurable customer impact. | Serve | 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 |
| Principal Researcher - Agentic AI - Microsoft Research AI Frontiers Principal Researcher focused on expanding AI capabilities, efficiency, and safety through innovations in foundation models and learning agent platforms. The role involves developing self-improving, adaptive agents for dynamic enterprise environments, integrating pre-training, post-training, RL, multi-agent collaboration, and deployment. Key responsibilities include research on recursive self-improvement, continual learning, human-AI collaboration, and building robust evaluation frameworks and synthetic data pipelines. | AgentData | 9 |
| Senior Researcher - Agentic AI - Microsoft Research AI Frontiers Research Scientist focused on agentic AI, developing self-improving, multi-agent systems that learn through interaction. The role involves research on recursive self-improvement, adaptive coordination, continual learning, human-AI collaboration, and autonomous skill acquisition. It spans the research-to-deployment spectrum with a focus on building evaluation frameworks and synthetic data pipelines, and refining architectures for scalability. The work is grounded in foundation models and learning agent platforms, with potential for product impact and publication. | AgentData | 9 |
| AI for Good Research Lab: Internship Opportunities Microsoft's AI for Good Research Lab is seeking PhD interns to conduct research in AI and data to address global challenges in areas like food security, disaster response, and conservation. The role involves formulating research questions, designing and implementing experiments with machine intelligence and ML, and collaborating on developing systems from prototype to production. Candidates should have a strong academic background in AI/ML, computer vision, or NLP, with experience in Python and deep learning models. | Post-train | 9 |
| Principal Applied Scientist Seeking a Principal Applied Scientist to research and develop novel AI agents, focusing on agentic systems, multi-step reasoning, and tool use. This role involves pushing the boundaries of AI agent capabilities and contributing to impactful AI products. | Agent | 9 |
| Research Intern - AI Frontiers - Reasoning & Agentic Models Research Intern position focused on advancing agentic model capabilities, including reasoning, tool use, and interaction across text and visual environments. The role involves developing novel training algorithms, exploring synthetic environments, multi-agent training, and scaling laws, with a focus on foundational models and modern architectures. The internship offers a chance to publish findings and potentially ship AI technologies in products. | AgentPost-train | 9 |
| Research Intern - Foundation Models and Agentic Systems Research intern role focused on advancing Generative AI and LLM technologies, specifically in foundation models and agentic systems. The work involves developing, improving, and exploring LLMs and Multimodal AI models, with research areas including reasoning, orchestration, multi-agent systems, and evaluation. | AgentPost-train | 9 |
| Senior Principal Researcher - Microsoft Research AI Frontiers Senior Principal Researcher at Microsoft Research AI Frontiers focused on pushing the boundaries of agentic AI, including large language and multimodal models, reasoning, and multi-agent systems. The role involves leading research, developing training methodologies, curating datasets, designing evaluation frameworks, and prototyping new agentic capabilities, with opportunities for publication and real-world impact. | AgentPost-train | 9 |
| Researcher - Multiple Levels, Microsoft Research AI Frontiers Research role focused on pushing the boundaries of agentic AI, large language, and multimodal models. The role involves developing cutting-edge training methodologies, curating datasets, designing evaluation frameworks, and prototyping new agentic capabilities. Emphasis on research, publication, and potential for real-world impact. | PretrainAgent | 9 |
| Research SDE II Research SDE II at Microsoft Research India focusing on advancing AI/ML innovation, including new models, scalable architectures, systems support, and large-scale applications. The role involves working closely with researchers and engineers, driving end-to-end research and development, and potentially mentoring interns. Requires strong coding and engineering skills, comfort with open problems, and a proven track record in AI/ML. | Post-trainServe | 9 |
| Principal Researcher - Artificial Specialized Intelligence - Microsoft Research Principal Researcher in Artificial Specialized Intelligence focusing on developing cutting-edge large foundation models and post-training techniques for specific domains and scenarios. The role involves integrating AI systems, developing research prototypes, and publishing findings in top-tier venues. | PretrainPost-train | 9 |
| Senior Researcher - Artificial Specialized Intelligence - Microsoft Research Senior Researcher at Microsoft Research focusing on Artificial Specialized Intelligence, developing cutting-edge large foundation models and post-training techniques for specific domains and real-world applications. The role involves conducting research, collaborating with cross-functional teams, developing prototypes, and publishing findings. | PretrainPost-train | 9 |
| Technical Advisor, Microsoft Superintelligence (Office of the CEO) Technical Advisor to the CEO of Microsoft AI, focusing on Humanist Superintelligence. The role involves providing strategic counsel, diving deep into research problems (model evaluation, prototyping, technical tradeoffs), and synthesizing insights for executive decision-making. It spans model development, infrastructure, safety, and alignment, requiring a blend of technical expertise and strategic advisory. | Post-trainServe | 9 |
| Research Intern - Foundations of GenAI Research Intern role focused on advancing Generative AI and Large Language Model Technologies, contributing to the development and exploration of LLMs and Multimodal AI models. The lab's mission is to expand AI capabilities, efficiency, and safety through innovations in foundation models and learning agent platforms, with research areas including reasoning, new architectures, action models, multi-agent systems, and evaluation. | PretrainAgent | 9 |
| Senior Researcher - AI Systems - Microsoft Research Senior Researcher in AI Systems at Microsoft Research, focusing on AI infrastructure, ML systems, and HPC systems to improve efficiency and scalability across the full AI model lifecycle, including pre-training, fine-tuning, post-training, and inference. | ServePost-train | 9 |
| Member of Technical Staff, AI Multimodal - MAI Superintelligence Team Research role focused on developing and training world-class multimodal AI frontier models, pushing boundaries of scale and performance. Involves algorithm development, model architecture design, experimentation, data innovation, and improving training/deployment efficiency. Collaborates with infrastructure, data engineering, pre-training, post-training, and product feedback teams. Requires strong publication track record and expertise in multimodal research. | PretrainPost-train | 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 |
| Research Intern - Machine Learning and Optimization Research Intern position focused on the intersection of Machine Learning, Optimization, and Large Language Models (LLMs) for efficient decision-making. Projects involve training LLMs for algorithm design, accelerating optimization algorithms, and using LLMs for sequential decision-making. The role involves designing algorithms/models, prototyping, conducting experiments, and potentially contributing to publications. | PretrainAgent | 9 |
| Research Intern - LLM Performance Optimization Research Intern role focused on optimizing the performance of Large Language Models (LLMs), involving architecture and inference performance. Requires PhD student status in a STEM field and experience with LLM architecture or inference performance optimization. Preferred qualifications include experience with GPU kernel performance bottlenecks and optimizing compiler architecture. | Serve | 9 |
| Research Software Engineer - Multiple Levels- AI Frontiers Research Software Engineer focused on Generative AI and agentic applications within Microsoft Research's AI Frontiers lab. The role involves developing, improving, and exploring capabilities of AI models and agentic systems, with a focus on creating reliable digital workers that can execute entire workflows and collaborate with humans and other agents. Key areas include enhancing agent reasoning, improving robustness, reimagining workflows for an agent-native world, and creating end-to-end experiences. | AgentData | 9 |
| Principal Research Engineer - Generative AI - AI Frontiers Research Engineer at Microsoft Research's AI Frontiers lab focused on advancing AI capabilities in modeling, algorithms, reasoning, and agentic AI. The role involves developing novel ideas in reinforcement learning, evolving pre-training and post-training codebases, and collaborating on state-of-the-art reasoning and agentic AI. Opportunities to ship research to Microsoft customers and expand AI capabilities, efficiency, and safety. | PretrainAgent | 9 |
| Research Intern - Diagnostic Imaging AI, Imaging Computing, Reconstruction and Inverse Problem Research Intern role focused on AI for medical image reconstruction and analysis. Involves developing new imaging AI model architectures, training methods, solving inverse problems for image reconstruction, and analyzing model performance including artifacts and hallucinations. Requires PhD enrollment, deep learning for imaging experience, and publication record. | Post-trainData | 9 |
| Research Intern - OneDrive and SharePoint (Summer 2026) Research intern to investigate, propose, implement, and evaluate new approaches in LLMs, Multimodal AI, Reinforcement Learning, Conversational AI, and AI Agents for OneDrive and SharePoint. Will conduct experiments, develop AI models, design evaluation metrics, build datasets, and deliver models for content understanding and use across various modalities. Focus on applying scientific methods to real-world problems in content and collaboration. | AgentData | 9 |
| Member of Technical Staff - Post-Training This role focuses on post-training methods for AI models, including continual pre-training, large-scale deep reinforcement learning, and data synthesis. The team works on language and multimodal models, with a focus on code-specific applications like Github Copilot. They also develop data infrastructure, tooling, and conduct research to improve model performance and impact. The role involves designing datasets, advancing model training, and ensuring data quality for cutting-edge AI. | Post-trainData | 9 |
| Member of Technical Staff - Post-Training This role focuses on advancing post-training methods for AI models, including continual pre-training, large-scale deep reinforcement learning, and fine-tuning. The team works on both OpenAI and open-source models, develops data infrastructure for large datasets, and creates tooling for dataset auditing. They also integrate language and multi-modality for products like Github Copilot and Visual Studio Code, with a mission to push the boundaries of AI toward Humanist Superintelligence. | Post-trainData | 9 |
| Member of Technical Staff - Machine Learning (AI Team) Research role focused on creating LLM models for general purpose capabilities and products, with a focus on agentive applications and advancing AI towards controllable, safety-aligned superintelligence. Responsibilities include developing new training methods, data collection, evaluation, and building user-facing features. | AgentPost-train | 9 |
| Member of Technical Staff - Machine Learning (AI Team) This role focuses on creating and improving LLM models for general-purpose capabilities and products, with a strong emphasis on agentive applications and safety alignment. The responsibilities include developing new training methods, collecting data, evaluating LLMs, building data flywheels, creating tooling for training/evals, writing production code, and developing new user-facing features. The role involves working on core LLM capabilities, fine-tuning, and training classifiers to support Microsoft products and APIs, with a specific focus on advancing towards 'Humanist Superintelligence' that is controllable and safety-aligned. | Post-trainAgent | 9 |
| Research Intern - AIP AI Knowledge Multimodal AI Research Intern role focusing on multimodal AI, specifically the synergy between vision and language. The intern will explore LLMs, SLMs, and VLMs for tasks like video understanding, document analysis, and multi-page QA, with hands-on experience in leveraging LLMs for document understanding, grounding, and retrieval-based generation. The role involves prototyping, experimenting, and publishing research. | Post-trainAgent | 9 |
| Research Intern - Deep Learning Group Research Intern position in Microsoft's Deep Learning group focusing on cutting-edge research in deep learning, AI, and related fields. The intern will collaborate with researchers, work on challenging problems, and potentially publish their findings. The role requires a PhD student with experience in Machine Learning, Deep Learning, and mathematical modeling. | Pretrain | 9 |
| Research Intern - Office of Applied Research Research intern position focusing on Generative AI, LLMs, NLP, Reinforcement Learning, and Human-Centered AI. The role involves research in areas like collaborative AI agents, multi-agent simulations, tool-use, learning from user feedback, synthetic data generation, LLM evaluation, and model fine-tuning. Requires a PhD program enrollment and research publication experience. | Post-trainAgent | 9 |