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 |
| 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 Principal Architect : Ads Trust & Safety AI Platform Senior Principal Architect for Microsoft Ads Trust & Safety AI Platform, defining and driving the next generation of AI systems for user protection, fraud prevention, and policy enforcement. This role involves architecting large-scale platforms for agentic investigation workflows, LLM reasoning, retrieval, model serving, and decisioning, requiring deep technical leadership and collaboration across multiple teams. | AgentServe | 9 |
| Principal Applied Scientist Principal Applied Scientist to define and develop next-gen intelligent, large-scale content platforms for AI-driven experiences. Responsibilities include modeling, experimentation, product impact, and technical leadership in areas like LLMs, information retrieval, ranking, grounding, search systems, and agentic AI. Focus on improving AI system information retrieval, reasoning, multi-turn conversations, tool use, response ranking, and grounded outputs. Requires hands-on experience tuning models at scale (SFT, preference optimization, distillation, data curation, evaluation, experimentation). Role involves leading scientific workstreams, influencing product direction, and collaborating with cross-functional teams. | AgentServe | 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 |
| 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 |
| Member of Technical Staff, Microsoft Robotics (Spatial AI) The Member of Technical Staff, Microsoft Robotics (Spatial AI) role focuses on designing, developing, and testing physical world models for robots to understand, predict, and reason about 3D physical environments. This involves building models for spatial structure, object relationships, physics dynamics, and scene semantics, enabling robots with physical intuition for manipulation, navigation, and interaction planning. The role contributes to world modeling, spatial AI, and foundation models for robotics, predicting physical world changes in response to robot actions. Responsibilities include designing and evaluating world models, building training data pipelines, and collaborating with researchers and engineers. | DataAgent | 9 |
| Member of Technical Staff, Microsoft Robotics (Robot Learning) Develop, train, evaluate, and deploy machine learning models for robots to perceive, reason, and act in the physical world, focusing on vision-language-action (VLA) and similar models. This role involves the full robot learning stack, from data pipelines and model experimentation to large-scale training and real-world deployment on physical robots. | ShipData | 9 |
| Principal Applied Scientist (CoreAI) The Principal Applied Scientist will drive the applied science foundation for observability in AI agents and multi-agent systems at scale. This role focuses on understanding agent behavior in production, developing scientific methods, evaluation frameworks, and measurement systems to diagnose and improve agent-based systems. Responsibilities include developing evaluation and measurement frameworks, designing methodologies to connect offline evals with online signals, defining quality signals and benchmarks for agent systems, building models for behavior analysis, advancing observability through new approaches, partnering with engineering to operationalize methods, and contributing to instrumentation standards. The role also involves technical leadership, setting scientific direction, and collaborating with product and platform teams. | AgentEval Gate | 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 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 |
| Principal Software Engineer, Foundry Agents - CoreAI Principal Software Engineer role focused on building foundational platforms for intelligent agents and generative AI systems. Responsibilities include developing large-scale, cloud-native systems for agent deployment, execution, tool integration, fine-tuning, training, observability, evaluation, and optimization in production. The role operates at the intersection of distributed systems, AI infrastructure, and developer platforms, requiring strong systems thinking and architectural decision-making for systems demanding high performance, reliability, security, and compliance. | AgentPost-train | 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 |
| 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 |
| Member of Technical Staff, Capacity & Efficiency Infrastructure - MAI Superintelligence Team This role focuses on optimizing and managing the compute infrastructure for training large-scale AI models. The responsibilities include designing and implementing distributed training systems, building telemetry for performance monitoring, profiling and debugging bottlenecks, and driving architectural improvements for efficiency. The role requires strong software engineering skills in Python and C++, deep understanding of GPU architectures, and experience with distributed computing systems and ML workloads. | Serve | 9 |
| Member of Technical Staff, Multimodal Infrastructure - MAI Superintelligence Team This role focuses on building and maintaining large-scale infrastructure for multimodal generative models, covering the full development cycle from data processing to training, inference, and serving. It involves working with research scientists and product engineers to optimize performance and drive architectural changes for consumer AI products like Copilot. | ServePost-train | 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 |
| 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 end-to-end performance and efficiency. It operates at the intersection of models, systems software, networking, storage, and AI hardware, influencing accelerator design, system architectures, and large-scale AI platforms. The role involves analyzing real workloads, developing performance models, and partnering with various teams to drive high-impact ideas into production systems. It also contributes to research and the broader community through publications and open-sourcing. | ServePretrain | 9 |
| 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 involves designing and curating high-quality text datasets, developing novel data collection strategies, improving dataset quality, understanding data-driven model behaviors, and aligning datasets with ethical values. Responsibilities include creating datasets for training and evaluation, developing scalable data pipelines, analyzing datasets, building tools for auditing, and collaborating with safety and ethics teams. | Data | 9 |
| Principal Product Manager, Agentic Experiences Product Manager for Agentic AI team, focusing on next-generation agentic AI products that reason, plan, and act across applications, the web, and the OS. The role involves translating AI research into scalable products for Copilot, Bing, Edge, M365, and Azure, with a focus on shipping 0-to-1 agentic products. | Agent | 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 |
| 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 |
| 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 |
| 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, Reinforcement Learning Systems - MAI Superintelligence Team This role focuses on designing, developing, and operating large-scale reinforcement learning systems for training agents and reasoning models. It involves contributing to cutting-edge research and bridging the gap between research and production-grade distributed systems, with responsibilities including tuning pretraining software for specific GPU architectures and contributing to AI model development. | PretrainPost-train | 9 |
| Member of Technical Staff - Multimodal - MAI Superintelligence Team This role is focused on building and advancing large-scale foundation models, with a specific emphasis on multimodal capabilities and ensuring AI systems are controllable, safety-aligned, and anchored to human values. The position involves algorithm development, model architecture design, experimentation, data pipeline innovation, and improving training/deployment efficiency, aiming to push the frontier of AI responsibly. | PretrainPost-train | 9 |
| Member of Technical Staff - Pre Training - MAI Superintelligence Team This role is focused on training frontier AI foundation models at Microsoft AI, specifically within the Pre-Training team of the Superintelligence Team. The responsibilities include developing algorithms, model architectures, data mixtures, and scaling laws for large-scale training, driving implementations, conducting experiments, and overseeing training runs. The role emphasizes collaboration with infrastructure, data, post-training, and multimodality teams. | Pretrain | 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 |
| Member of Technical Staff, Evaluations Engineering - MAI Superintelligence Team This role focuses on building and scaling the evaluation infrastructure for generative AI models on large-scale GPU clusters. It involves developing sophisticated tools and techniques for reliability, performance, and health monitoring, and collaborating with model scientists on evaluation methods and inference strategies. The role also touches on pretraining software development and benchmarking. | Eval GateServe | 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 |
| Member of Technical Staff, Pre-Training Infrastructure - MAI Superintelligence Team This role focuses on building and optimizing the software stack for massive GPU clusters, high-throughput storage systems, and cutting-edge AI research. You will work closely with model scientists to scale up the latest research recipes, implement new forms of distributed training parallelism, and ensure the reliability and performance of thousands of GPUs across our supercomputing fleet. Profiling, benchmarking, debugging, and fine-grained optimization are core to this role, demanding both engineering rigor and creativity. | Pretrain | 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 - 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 |
| 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 - 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 - 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 - 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 |
| Senior Software Engineer Senior Software Engineer role focused on designing, shipping, and operating agentic support platforms and AI-driven autonomous support workflows for Microsoft's commercial business. The role involves end-to-end ownership of features, including orchestration, grounding, evals, observability, and SDK surfaces, with a strong emphasis on reliability, trustworthiness, and scalability of AI-managed support systems. | Agent | 8 |
| AI Chief Technology Officer - SME&C AI Chief Technology Officer (CTO) for the Small, Medium Enterprises & Channel (SME&C) segment in ANZ. This role is the senior AI technical voice, responsible for evangelizing AI and Data across the segment, engaging with C-suite leaders, driving customer adoption, and leading the development of strategic partnerships. The mandate spans AI experiences (Copilot, Azure AI), data platforms (Microsoft Fabric), and security, aiming to unlock growth and business transformation for customers. | Ship | 8 |
