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 - 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 |
| 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 |
| Technical Program Manager - Generalist (AI/ML) Technical Program Manager for Microsoft AI's Superintelligence Team, focused on training frontier AI models. The role involves end-to-end program planning, coordinating with researchers and engineers, managing timelines, mitigating risks, and ensuring the responsible advancement of AI. | Pretrain | 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 |
| Member of Technical Staff - Machine Learning (AI Team) This role focuses on developing and improving LLM models for general-purpose capabilities and products, with a strong emphasis on agentive experiences. Responsibilities include data acquisition/generation, generalizing ML solutions, leading evaluation efforts, adapting state-of-the-art research, and writing production-quality code. The role involves fine-tuning, training classifiers, and engineering prompts, aiming to push the boundaries of AI towards controllable, safety-aligned superintelligence. | 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 |
| 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 |
| 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 |
| 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 |
| 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 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 |
| 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 |
| 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 |
| Principal Applied Scientist Principal Applied Scientist to lead the development of ML and generative AI systems for conversational commerce experiences within Microsoft Copilot. The role involves product discovery, ranking, personalization, reasoning, LLM-based systems, RAG, tool orchestration, and addressing quality/trust challenges, with a focus on shipping low-latency, reliable user-facing features. Technical leadership and Responsible AI practices are also key. | AgentServe | 8 |
| Software Engineer II Software Engineer II role on the Azure AI Foundry Customization team, focused on building and scaling the AI platform for Azure and Microsoft's flagship products. The role involves developing pre-training, mid-training, and post-training solutions, working with LoRA models, and handling inference at scale. Responsibilities include creating abstractions, infrastructure, and features for training, testing, validation, scaling, and optimization of ML algorithms, as well as driving customer-inspired innovations and ensuring code quality and security. | Post-trainServe | 8 |
| Principal Software Engineer - CoreAI Principal Software Engineer to build and operate end-to-end multimodal generative AI systems for Azure Content Understanding, focusing on extracting insights from diverse data types. The role involves technical leadership, system design, quality improvement through evaluation, and collaboration with security and product teams. | ShipAgent | 8 |
| Principal Architect - Data AI This role focuses on architecting, designing, and delivering AI-driven transformation solutions for enterprise customers, with a strong emphasis on Azure AI services, machine learning models (including generative AI and LLMs), and AI agentic frameworks. The architect will lead client engagements, ensure solution performance and scalability, and guide customers through the deployment and operationalization of AI solutions. | AgentServe | 8 |
| 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 |
| Principal Software Engineer, Security AI Principal Software Engineer focused on building AI-powered security systems for Microsoft's cloud environment. The role involves designing, building, and operating production AI services that combine LLMs, agentic workflows, RAG, knowledge graphs, and multi-modal processing, with a strong emphasis on evaluation, responsible AI, and scalability within a large cloud platform. The candidate will lead architecture, design, and delivery of these systems, collaborating across various teams to translate AI advances into practical security solutions. | AgentServe | 8 |
| AI Engineer II & Senior AI Engineer - Getting Customers Ready for AI AI Engineer role focused on designing, building, and deploying AI-native systems for enterprise customers to securely adopt AI at scale. This involves working across the AI lifecycle, including model development, data pipelines, deployment, monitoring, and MLOps, with a focus on LLM-based applications, RAG, and agentic workflows within a security context. | AgentServe | 8 |
| Sr Software Engineer Senior Software Engineer to design and ship core components of an Agentic support platform, owning features end-to-end from prototype to production. Responsibilities include working across orchestration, grounding, evals, observability, and SDK surfaces, while ensuring production-readiness, trustworthiness, and scalability of AI-managed support systems. | Agent | 8 |