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 |
|---|---|---|
| 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 |
| Research Intern - Self-Improving AI Research Intern position focused on self-improving AI systems, involving language modeling and reinforcement learning. The role is part of Microsoft Research NYC and requires enrollment in a PhD or master's program with experience in deep learning, language modeling, and/or reinforcement learning. Preferred qualifications include experience with deep learning frameworks like PyTorch and Hugging Face Transformers. |
| Post-trainAgent |
| 9 |
| Research 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 - 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 |
| 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 - 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 |
| 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 |
| Applied Scientist II Applied Scientist II at Microsoft AI focusing on Generative AI and Agentic Modeling for consumer products like Bing and Copilot. The role involves building and optimizing production ML models, working with SOTA generative models, analyzing large-scale data, designing experiments, and delivering insights for business decisions. Requires expertise in ML, Generative AI, Agentic Modeling, or Data Science, with hands-on experience with LLMs/SLMs. | Post-trainAgent | 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 |
| Principal Applied Scientist This role focuses on building and leading the development of advanced multilingual speech models, AOAI finetuning, and multimodal generative AI for Microsoft's Azure Speech team. The goal is to create transformative speech technologies for voice agents, transcription, and call centre analytics, impacting billions of users globally, with a special focus on India. The role involves setting technical direction, driving innovation, scaling model quality, and delivering breakthrough technologies. | Post-trainServe | 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 |
| 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 |
| 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 |
| 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 - 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 |
| Applied Scientist II / Senior Applied Scientist - Responsible AI (CoreAI) The role focuses on building and scaling Responsible AI service components, specifically involving supervised fine-tuning of LLMs with RLHF, conducting evaluations, and developing agent adversarial evaluations and safety mitigations. The goal is to enable customers to use AI responsibly and securely. | Post-trainAgent | 8 |
| Principal Machine Learning Engineer Principal Machine Learning Engineer for Health Futures team focused on accelerating training of generative models, advancing model capabilities, and optimizing training/evaluation/inference pipelines for health and life sciences applications. | Post-trainServe | 8 |
| Member of Technical Staff - Post Training - MAI Superintelligence Team This role focuses on the post-training of large language models (LLMs) to improve their capabilities in areas like reasoning, instruction following, math, code, and tool use. The responsibilities include data collection, building evaluations, and applying advanced reward modeling and RL techniques. The goal is to advance the state-of-the-art in LLM performance and contribute to the development of superintelligent AI systems. | Post-train | 8 |
| Research Intern - Computer Vision and Deep Learning Research Intern position focused on computer vision and deep learning to improve user understanding of the environment and human-computer interactions. Involves analyzing multimodal sensor data and pushing the state of the art in the field. | Post-train | 8 |
| Applied Sciences PhD This role focuses on advancing the state-of-the-art in AI/ML research and driving innovation from theory into reality by blending research and development techniques. The individual will work on the design, development, execution, and implementation of technology research projects, with a focus on technology transfer into products and services. The role requires a PhD student in a related field and involves understanding research literature, preparing data for analysis, and contributing to patents and white papers. | Post-train | 7 |
| Principal Software Engineering Manager This role is for a Principal Software Engineering Manager within Microsoft's AI Platform organization, specifically on the AI Foundry OSS Model Customization Team. The team focuses on enabling data scientists and developers to build, train, deploy, and manage machine learning models, with a specialization in customizing open-source models. The manager will lead and develop a team of engineers, focusing on scalable services, customer needs, and career development, while collaborating with external partners and internal Microsoft teams. A strong background in Generative AI, ML, deep learning, NLP, transformer models, and cloud platforms is required. | Post-train | 7 |
| Research Sciences INTERN Research intern to conduct research and lead collaborations on incorporating AI capabilities into Azure SQL Database platform. Focus on advancing state-of-the-art in machine intelligence and machine learning applications, implementing prototypes, and developing solutions for large-scale problems. Experience with LLMs and ML techniques is preferred. | Post-trainServe | 7 |
| Senior Researcher - AI and Systems Reliability - Microsoft Research Senior Researcher at Microsoft Research focusing on AI and Systems Reliability. The role involves defining a novel research agenda in areas like distributed systems, formal methods, ML for system reliability, and reliability of ML systems, with the goal of bringing formal rigor and reliability guarantees to AI-powered platforms. | Post-train | 7 |
| Research Intern - MSR Inclusive Futures Team Research Intern position at Microsoft Research's Inclusive Futures group, focusing on needs-focused research for underserved individuals. Requires a PhD student in a relevant STEM field with experience in HCI, AI, Accessibility, or related areas. The role involves conducting original research, collaborating with researchers, and potentially publishing findings. | Post-train | 7 |
| Research Intern - Technology for Religious Empowerment Research Intern position focusing on adapting and designing AI systems for religious communities, involving model evaluations, product design, and responsible AI practices. The role requires a PhD student in a STEM field with an interest in religion and experience with emerging technologies like Generative AI and Agentic Systems. | Post-trainAgent | 7 |
| Research Intern - Gray Systems Lab (GSL) Research intern role focusing on machine learning for systems, reinforcement learning, natural language-to-query, and agentic workflows within Azure Data's Gray Systems Lab. The internship involves research and development for databases, big-data, and cloud systems, with potential impact on production systems and publications. | Post-trainAgent | 7 |