Currently tracking 250 active AI roles, down 24% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$331k (avg $195k).
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.
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 |
| 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 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 |
| 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 |
| 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 |
| 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 |
| 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 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 |
| Principal Research Engineer - Agent 365 Principal Research Engineer role focused on architecting and delivering scalable AI systems for Microsoft 365 Copilot experiences, including foundational models, multi-agent systems, and RAG. The role involves technical leadership, driving innovation, production integration, evaluation, and ensuring responsible AI practices. It requires experience with LLMs, multimodal models, multi-agent architectures, and RAG, with a focus on end-to-end ML pipelines and deployment at scale. | AgentServe | 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 |
| Senior Research Engineer Senior Research Engineer to design, implement, and ship research-driven solutions for autonomous agents, focusing on human oversight, assistance, and management within business processes. The role involves integrating agents, humans, and applications to streamline business processes and shape the future of human-AI collaboration. | Agent | 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 |
| 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 |
| Principal Product Manager, Foundational AI Research The Principal Product Manager, Foundational AI Research role at Microsoft AI focuses on advancing the next generation of LLM models. Responsibilities include working on pre-training/post-training data and evaluations, training infrastructure, or API/Platform. The role involves prioritizing research based on customer needs, building evaluations and datasets, and collaborating with AI researchers to execute project plans. Experience in building data collection or evaluation pipelines for AI models and collaborating with ML researchers/engineers is required. | PretrainPost-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 |
| Senior and Principal Applied Scientists - CoreAI This role focuses on the applied science foundation for observability in AI agents and multi-agent systems running at scale. It involves developing and applying scientific methods, evaluation frameworks, and measurement systems to understand, benchmark, diagnose, and improve agent-based systems in production. The role addresses unique observability challenges of AI agents, such as non-deterministic execution and emergent behaviors. | AgentEval Gate | 9 |
| Principal Product Manager, AI Model Security Product Manager for AI Model Security within Microsoft's Superintelligence Team, focusing on hardening frontier LLMs against security threats (prompt injection, jailbreaking, data exfiltration, etc.) and ensuring models deliver capabilities for real-world security workflows. This role involves defining the security roadmap, driving exploit defense, building red-teaming frameworks, partnering with security product teams, and shaping launch readiness, with a strong emphasis on understanding attacker perspectives and balancing capability with risk. | Post-trainAgent | 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 |
| 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 |
| Applied Scientist II This role focuses on building and evolving the core orchestration and intelligent systems that power Microsoft's enterprise Copilot, a large-scale AI assistant for Microsoft 365. The work involves advancing model training, developing model-driven features from concept to production, and enhancing the orchestrator for improved reasoning, speed, and multi-modal/agentic capabilities. The goal is to ship cutting-edge AI technology impacting hundreds of millions of users. | AgentPost-train | 9 |
| Senior Software Engineer, CoreAI Senior Software Engineer on the FIT training team within Microsoft's CoreAI organization, focused on building and optimizing AI infrastructure for agentic AI systems. The role involves developing scalable infrastructure for training LLMs, SLMs, and agentic models to achieve frontier-level performance, contributing to both proprietary and open-source frameworks for enterprise-grade agentic workflows. | DataAgent | 9 |
| Principal Software Engineer, CoreAI This role focuses on building and optimizing the AI infrastructure for training agentic AI systems, including LLMs and SLMs, to achieve frontier-level performance. It involves developing scalable infrastructure and services for training, deploying, and monitoring these models in a cloud environment. | DataAgent | 9 |
| Member of Technical Staff, Principal Tech Lead Manager, Image Generation Principal Tech Lead Manager for Copilot's image generation capabilities, focusing on technical leadership, product delivery, evaluation systems, and team building. This role involves defining the technical roadmap, integrating new models, scaling evaluation frameworks, and leading a team of AI engineers to improve image quality and user satisfaction in a high-impact consumer product. | ShipEval Gate | 9 |
| Senior Software Engineer, CoreAI The AI Core Infrastructure team is responsible for building and managing the large-scale GPU management infrastructure and inference/training platforms that power Microsoft's AI workloads. This role focuses on the training infrastructure for large-scale model pre-training, post-training, and fine-tuning on advanced GPUs in Azure and partner clouds. | PretrainPost-train | 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 |
| 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 |
| 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 |
| 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 - Data Scientist Data Scientist role focused on building next-generation post-training methods for frontier models at Microsoft AI. Responsibilities include designing evaluations, producing high-quality training data, building scalable data pipelines, and running post-training experiments to improve model capabilities like instruction following, coding, and agentic behaviors. The role operates across the full post-training lifecycle, from data generation to reward modeling and reinforcement learning, with a focus on turning raw model capability into reliable and measurable performance improvements. | Post-trainData | 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 |