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 Software Development Engineer Microsoft Research India is seeking research engineers with a demonstrated track record in AI/ML, including new models, scalable ML architectures, systems support for such workloads, and innovative large-scale applications of ML models. The role involves working closely with researchers and engineers, comfortable with open problems and changing requirements, and driving end-to-end research and development from ideation to deployment. | Post-trainServe | 9 |
| Research Intern - Memory & Orchestration in Large Language Models Research intern role focused on developing new LLM memory representation and orchestration systems, including advanced RAG and embedding techniques, for enterprise and consumer applications. | Agent |
| 9 |
| Senior Researcher - AI Agents - Microsoft Research Senior Researcher focused on advancing state-of-the-art in agentic systems and ecosystems, including building agent-native ecosystems, developing advanced agentic capabilities through post-training methods, creating novel human-agent interaction techniques, and developing evaluation benchmarks and tooling for agents. The role emphasizes outcome-driven innovation, collaborative innovation, problem-solving, decision-making, and the scientific method, with a strong publication policy and potential for shipping AI technologies. | AgentPost-train | 9 |
| Senior Researcher - Multimodal AI - Microsoft Research AI Frontiers Senior Researcher in Microsoft Research AI Frontiers lab focusing on expanding AI capabilities, efficiency, and safety through innovations in foundation models and learning agent platforms. The role involves research into Generative AI and Multimodal Model (MLM) technologies, including reasoning, architectures, training methods, action models, orchestration, multi-agent systems, and evaluation. | PretrainAgent | 9 |
| Research Engineer - Generative AI - AI Frontiers Research Engineer role 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, mid-training, and post-training codebases for LLMs, and contributing to reasoning and agentic AI research. Opportunities to ship research to Microsoft customers. | Post-trainAgent | 9 |
| Senior Researcher - Artificial Intelligence - Microsoft Research Senior Researcher in Microsoft Research's AI Interaction and Learning team, focusing on collaborative AI systems where humans and AI agents work together. The role involves pushing the boundaries of learning and reasoning with foundation models, developing innovative AI/ML techniques, and shaping the team's research agenda. Key interests include designing metrics for evolving goals, eliciting preferences under uncertainty, and managing information flow for coordination. The role requires a PhD and experience in areas like Foundation Models, RL, NLP, and Deep Learning, with a strong publication record in top-tier venues. | PretrainAgent | 9 |
| Senior Researcher - Generative AI - Microsoft Research AI Frontiers Senior Researcher in Generative AI at Microsoft Research AI Frontiers, focusing on expanding AI capabilities, efficiency, and safety through innovations in foundation models and learning agent platforms. The role involves leading research in Generative AI and LLMs, with projects including Small Language Models and agentic AI systems. Key research areas include reasoning, action models for tasks, and evaluation of model/agent capabilities. The position offers a vibrant research environment with an open publication policy and opportunities for real-world impact. | PretrainAgent | 9 |
| Senior Researcher - Artificial Specialized Intelligence, Microsoft Research Senior 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 conducting research, collaborating with cross-functional teams, developing prototypes, and publishing findings. | Post-trainPretrain | 9 |
| Research Intern - Microsoft Research Special Projects Research intern focused on advancing Large Language Model (LLM) capabilities, specifically in areas like memory representations, retrieval methods (e.g., GraphRAG), handling temporal changes, ambiguity, and hallucination detection/mitigation. | Post-trainAgent | 9 |
| Research Intern - Machine Learning and Optimization - Redmond Research intern position focusing on the intersection of Machine Learning and Optimization, specifically combining Large Language Models (LLMs) with optimization for efficient decision-making. Projects involve training LLMs for algorithm design, accelerating optimization algorithms, and using LLMs for sequential/distributed decision-making. The role involves designing algorithms/models, prototyping, conducting experiments, and analyzing results, with potential contributions to papers. | Post-trainAgent | 9 |
| Research Intern - Training Methods for LLM Efficiency Research intern to design and apply training algorithms for improving the quality/efficiency trade-offs of large language models, focusing on resource-constrained environments. Potential research directions include quantized model fine-tuning, improving token efficiency for reasoning models, and scaling training under resource constraints. | Post-trainData | 9 |
| Research Intern - Model Optimization and HW Acceleration Research Intern role focusing on optimizing LLMs, VLMs, and generative models, with an emphasis on hardware acceleration. The role involves designing experiments, developing algorithms, and collaborating on practical solutions, aiming to advance AI technologies. | Post-trainServe | 9 |
| Research Intern - Multimodal Language Models Research intern to explore efficient multimodal language models using techniques like model compression, quantization, and optimization for resource-constrained platforms. Focus on training strategies for vision-language tasks, prototype implementation, experiment design, and result analysis. | Post-trainServe | 9 |
| Researcher Researcher at Microsoft Research Asia (MSRA) in Singapore focusing on Foundation Model innovations (LLM, vision, multi-modality), Deep Learning and Reinforcement Learning Foundation, and Industrial AI applications like Healthcare and Embodied AI/Robotics. Conducts research to advance state-of-the-art, formulates research problems, and initiates research agendas. Bridges research and development, potentially creating long-term business opportunities, but not responsible for immediate product needs. | Pretrain | 9 |
| Researcher Researcher at Microsoft focusing on advancing the state-of-the-art in AI, Computer Systems, Networking, NLU, Computer Vision, and ML. The role involves conducting research, leading collaborations, formulating research problems, and developing prototypes. While expertise is provided to product groups, the primary focus is on academic knowledge advancement rather than immediate product needs. The role requires strong programming skills, depth of knowledge in AI fields, and experience in research execution and publication. | Pretrain | 9 |
| Research Intern - Fundamentals of AI: Security, Agents, Systems & Control Research Intern role focused on advancing core AI research in security, agentic workflows, and next-generation architectures. Key areas include strengthening AI robustness, designing post-training alignment strategies for multi-turn interactions, and investigating novel architectures beyond transformers. The role involves fundamental research and system-level applications, leveraging shared resources and evaluation frameworks. | Post-trainAgent | 9 |
| Research Intern - AI Frontiers - Reasoning & Agentic Models Research intern role focused on advancing agentic model capabilities, including reasoning, tool use, and end-to-end workflow execution across text and visual environments. The role involves research in reinforcement learning, novel training algorithms, synthetic environment creation, multi-agent training, and scaling laws, with a focus on foundational models and various data modalities. The internship aims to contribute to cutting-edge research and potentially ship AI technologies in products. | AgentPost-train | 9 |
| Research Intern - Machine Learning and Statistics Research Intern position in Machine Learning and Statistics at Microsoft Research New England, focusing on advancing the state-of-the-art in applied and theoretical ML research. Projects cover a broad range of ML topics including generative models, transfer learning, optimal transport, reinforcement learning, and deep learning. | Pretrain | 9 |
| Research Intern - Artificial Intelligence Research Intern position at Microsoft Research focusing on artificial intelligence projects including multimodality, world models, LLMs, and computer vision. The role involves conducting research, developing novel methodologies, and disseminating findings through publications. Requires enrollment in a master's or PhD program. | Pretrain | 9 |
| Research Intern - Artificial Intelligence Research Intern position at Microsoft focusing on advancing artificial intelligence through research in areas like multimodality, world models, LLMs, computer vision, AI4Code, robotics, and agents. The role involves conducting research, developing novel methodologies, and disseminating findings through publications. | Pretrain | 9 |
| Research Intern - Systems for Reliable and Scalable AI Agents Research Intern position focused on building reliable, safe, and efficient AI agents. The role involves exploring formal verification, reliability, safety, intelligent task handling, secure execution, and efficiency optimization for AI agents. It is a research-focused role within Microsoft Research, aiming to tackle complex challenges in AI agent systems. | Agent | 9 |
| Research Intern - MSR AI Interaction and Learning Research intern role focused on advancing next-gen AI systems where humans and AI agents collaborate. The role involves research in areas like foundation models, reinforcement learning, multi-objective optimization, NLP, deep learning, interactive learning, agents, causal reasoning, computational social science, and human-AI collaboration, with a focus on shifting AI systems development towards optimizing complex objectives like group-level outcomes and team coordination. The internship is 12 weeks and involves collaboration with researchers and presenting findings. | PretrainAgent | 9 |
| Research Intern - Machine Learning at MSR NYC Research Intern at Microsoft Research NYC focusing on machine learning and artificial intelligence, with specific interests in reinforcement learning for language models, science of deep learning, post-training, reasoning, and test-time scaling. The role involves collaborating with researchers, presenting findings, and contributing to research projects over a 12-week internship. | Post-train | 9 |
| Research Intern - Foundations of Generative AI Research Intern position at Microsoft Research AI Frontiers lab focusing on expanding AI capabilities, efficiency, and safety through innovations in foundation models and learning agent platforms. The role involves developing, improving, and exploring LLMs and Multimodal AI models, with research areas including reasoning, new architectures, action models, multi-agent systems, and evaluation. | PretrainAgent | 9 |
| Technical Solution Management Specialist - AI Evaluation, Research, and Technical Architecture Func. This role focuses on establishing and operating an AI Innovation Lab within Microsoft's Customer Experience and Success organization. The primary responsibility is to research, validate, and evaluate early-stage AI opportunities (pre 0-to-1) before they are handed off for prototyping or product engagement. This involves defining research frameworks, building evaluation approaches for various AI workloads, developing automated testing, and creating reference architectures. The role acts as a bridge between business strategy, research, and technical execution, ensuring AI innovations are rigorously tested and aligned with Responsible AI standards. | Eval GateData | 8 |
| Senior Researcher, Office Product Group Senior Researcher role within the Office Product Group focused on advancing AI-powered experiences in Microsoft 365 applications. The role involves designing, developing, evaluating, and deploying AI systems that can reason and act across tools and documents, balancing innovation with production readiness. | AgentPost-train | 8 |
| Principal Applied Scientist Principal Applied Scientist role at Microsoft AI Web Data team focused on building the data foundation for Bing and Microsoft AI experiences, including large-scale grounding and LLM training. The role involves translating research into production, advancing state-of-the-art modeling, and deploying algorithms and solutions to improve system performance, quality, data management, and accuracy. | Post-trainPretrain | 8 |
| Principal Applied Scientist This role focuses on building the data foundation for Bing and Microsoft AI, involving large-scale grounding and LLM training. The Principal Applied Scientist will translate research into production, developing and deploying algorithms and solutions to improve system performance, quality, data management, and accuracy. The role emphasizes developing deep expertise, partnering with stakeholders, mentoring junior talent, and collaborating across teams to shape the future of AI. | DataPost-train | 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 |
| Senior Applied Scientist and Principal Applied Scientist This role focuses on developing and industrializing deep learning speech technologies, with a specific emphasis on integrating speech with LLMs for multimodal modeling. The scientist will invent new algorithms, apply them to real products, and evaluate their performance against guardrails, impacting millions of users. | Post-trainServe | 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 |
| Applied Researcher 2/ Senior Applied Researcher Applied Researcher role focused on post-training code specific models and agentic research for developer tools like Github Copilot and VS Code. The role involves building and managing large-scale ML experiments, creating new datasets, and collaborating with product teams to take research from concept to product. | Post-trainAgent | 8 |
| Machine Learning Scientist II This role focuses on researching and developing machine learning models, specifically large language models (LLMs), for Microsoft 365 Copilot. The core responsibilities involve advancing research through projects, developing new algorithms and prototypes, and collaborating with product groups and Microsoft Research. The role emphasizes fine-tuning models for specific applications and contributing to the AI platform infrastructure that enables Copilot workflows. The position requires expertise in LLMs, deep learning, and responsible AI, with a strong emphasis on shipping applied research to production. | Post-trainServe | 8 |
| Security Research Intern - AI Focus AI Security Research Intern focused on developing autonomous systems to detect and disrupt cyber attacks in near real-time, leveraging LLMs and agentic frameworks. | Agent | 8 |
| Applied Scientist II Applied Scientist II role at Microsoft focusing on integrating AI research into productivity products like M365 Copilot. The role involves defining and leading research projects, collaborating with cross-functional teams, and contributing to the scientific community through publications. Research areas include reinforcement learning, agentic systems, multimodal modeling, post-training techniques, and LLM applications. | Post-trainAgent | 8 |
| Principal Applied Scientist Principal Applied Scientist role at Microsoft AI Web Data team, focusing on building the data foundation for Bing and Microsoft AI experiences. This involves large-scale grounding, LLM training, and end-to-end processing of web content. The role translates research into production, advancing state-of-the-art modeling and deploying algorithms to improve system performance and accuracy. | Post-trainPretrain | 8 |
| Senior Researcher - Efficient AI Senior Researcher focused on advancing efficiency across the AI stack for generative AI serving systems, spanning models, ML frameworks, cloud infrastructure, and hardware. The role involves algorithmic and systems optimization for latency, throughput, and cost, with a strong emphasis on driving research ideas through prototyping, validation, and production deployment. | ServePost-train | 8 |
| Research Intern - Computer Vision and Deep Learning Research intern position focused on computer vision and deep learning to improve user understanding of devices and environments. Involves analyzing multimodal sensor data and human-object interactions to enhance human-computer interactions, with opportunities to advance the state of the art. | Data | 8 |
| Principal Applied Scientist - CoreAI The Principal Applied Scientist will develop machine learning techniques for safety, alignment, and trustworthy AI, collaborating across teams to build and maintain responsible AI systems from development to production. This role focuses on the application and improvement of AI models, particularly large language models, within Microsoft's CoreAI organization. | Post-train | 8 |
| Research Intern - AI Safety and Security Research intern position focused on LLM safety and security, involving research into protecting LLMs from malicious inputs and using LLMs for computer security. The role involves collaboration with researchers and contributing to research publications. | Post-trainAgent | 8 |
| Senior Researcher - Machine Learning - Microsoft Research Senior Researcher in Machine Learning within Microsoft Research's Health Futures organization, focusing on advancing AI for biomedicine and life sciences discovery. The role involves designing, implementing, and evaluating novel AI methodologies, including post-training, inference-time optimization, and interpretability techniques. | Post-trainServe | 8 |
| Research Intern - AI Safety & Reliability for LLM Systems Research intern to study LLM-based assistants' behavior with incomplete information, focusing on uncertainty awareness, responsible reasoning, and robustness for enterprise AI systems. | Agent | 8 |
| Applied Researcher 2/ Senior Applied Researcher Applied Researcher role focused on post-training code specific models and agentic research for developer tools like Github Copilot. The role involves building and managing ML experiments, creating datasets, and collaborating with product teams to apply and advance LLM approaches for software engineering, including RAG and evaluation, with opportunities to ship AI advancements to millions of developers. | Post-trainAgent | 8 |
| Sr Research Scientist Senior Research Scientist to lead cutting-edge projects from concept to product, focusing on AI for Developers. This role involves building and training state-of-the-art models, applying and advancing techniques for leveraging LLMs in software engineering (including RAG and evaluation), and collaborating with product teams to run large-scale experiments and improve AI solutions. The primary focus is on AI for code completion and editing, retrieval-augmented systems for codebases, and efficient inference algorithms for code generation. | AgentServe | 8 |
| Senior Researcher - Machine Learning for Life Sciences - Microsoft Research Senior Researcher in Machine Learning for Life Sciences at Microsoft Research, focusing on advancing AI for biomedicine and life sciences discovery. The role involves designing, implementing, and evaluating novel AI methodologies, including post-training, inference-time optimization, interpretability, and experimental design. It also requires application-specific benchmarking, interpretation of deep learning models on biological data, and developing approaches for inference-time optimization. | Post-trainServe | 8 |
| Research Intern - Applied Speech Research Research Intern role focused on applied speech research within the Health and Life Sciences group at Microsoft. The internship involves leveraging AI and speech technologies to improve healthcare outcomes and operations, with a focus on speech recognition, synthesis, and understanding. The role is for PhD candidates in Computer Science or related STEM fields. | Post-train | 8 |
| Research Intern - Agentic Programming Research Intern role focused on agentic programming, involving building agentic workflows and ML models for software engineering tasks, within a PhD program context. | Agent | 8 |
| Senior Researcher - AI & Society - Microsoft Research Senior Researcher at Microsoft Research focusing on the intersection of AI systems and society, with an emphasis on sociotechnical approaches to AI evaluation, responsible AI in industry, and AI safety. The role involves interdisciplinary research, collaboration with industry teams, and a strong publication record. | Eval Gate | 8 |
| Research Intern - Applied Sciences Group Research intern to investigate Small Language Model (SLM) architectures and techniques, such as recurrent transformers and universal transformers, for maximizing LLM throughput with limited cache on hardware targets like SoCs, GPUs, or NPUs. Will involve model training at scale using Azure compute and collaboration with a multidisciplinary team. | Post-trainServe | 8 |
| Senior Researcher - GPU Performance Applied Research role focused on hardware/software codesign for GPU kernel optimizations to improve efficiency of Large Language Models and Generative AI inference. Involves designing, implementing, and optimizing GPU kernels, researching novel optimization techniques, and profiling performance. | Serve | 8 |