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 |
|---|---|---|
| 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 |
| Member of Technical Staff, AI Post-Training - MAI Superintelligence Team Post-Training - Develops and ships post-training methods for large language models (LLMs) used in Microsoft Copilot, focusing on data collection, evaluation, finetuning algorithms, and prototyping new capabilities. Collaborates with pretraining and product platform teams to deploy models and improve them based on user feedback. |
| Post-train |
| 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 |
| 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 |
| Senior Software Engineer Senior Software Engineer role on the Foundry Agents team at Microsoft CoreAI, focusing on building a platform for Azure AI customization. The role involves end-to-end ownership of systems that enable AI to learn, improve, and scale in production, including pre-training, mid-training, and post-training solutions, LoRA model deployment, and large-scale inferencing. Responsibilities include developing ML algorithms, infrastructure, and features for training, testing, validation, scaling, and optimization, with a focus on making agentic AI economically viable for enterprises. | 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 |
| 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 |
| Senior Applied Scientist Senior Applied Scientist role focused on developing and shipping innovative machine learning solutions, particularly large language models and conversational search experiences, for Microsoft products. Responsibilities include training models, creating evaluation sets and infrastructure, fine-tuning LLMs, and driving projects from design to implementation and shipping. The role involves deep data analysis, prompt engineering, and setting up engineering pipelines. Experience with production systems and end-to-end AI product development is emphasized. | Post-trainServe | 8 |
| Senior Applied Scientist Senior Applied Scientist role focused on developing advanced multilingual speech models, LLM speech finetuning, and multimodal generative AI for real-time transcription, intelligent voice agents, and multilingual speech solutions within Microsoft's Azure Speech team. The role involves setting technical directions, building novel data generation solutions, and collaborating with global teams to deliver impactful speech technologies for Microsoft products and enterprise solutions, with a focus on India. | Post-trainAgent | 8 |
| Senior Applied Scientists and Principal Applied Scientists (Multiple Positions) - Copilot Tuning Seeking Senior/Principal Applied Scientists to fine-tune LLMs on tenant data for M365 Copilot, creating task-specific agents and solutions. Role involves writing training pipelines, designing experiments, implementing inference solutions, and shipping models to customers. Focus on advancing LLM capabilities in an enterprise context. | 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 |
| Sr. Data Scientist Senior Data Scientist for Windows at Microsoft Hyderabad. Focuses on using advanced analytics, modeling, and data science to inform decision-making, optimize product performance, and maximize business impact for Windows products. Key responsibilities include improving search relevance, fine-tuning foundational models, driving growth through predictive insights, and leading initiatives in evaluation, corpus creation, metric design, and dataset development for diverse modalities. The role involves analyzing data, designing experiments, and deriving insights to influence product development and business strategy. | Post-trainAgent | 7 |
| Senior Data Scientist Senior Data Scientist role focused on developing and deploying AI/ML models for enterprise customers, involving data acquisition, model evaluation, and operationalization at scale. The role emphasizes customer collaboration and building impactful solution patterns. | Post-train | 7 |
| Data Scientist 2 Data Scientist role focused on applying machine learning and statistical analysis to develop, train, optimize, and evaluate models for enterprise customers. The role involves data preparation, model evaluation, and integrating these models into customer systems, with a strong emphasis on Responsible AI. | Post-train | 7 |
| Applied Data Scientist II This role focuses on developing and operationalizing machine learning models for threat detection within Microsoft's security ecosystem. It involves building supervised and unsupervised models, applying graph-focused ML techniques, and analyzing large security datasets. The role also includes data engineering for feature pipelines and running experiments to improve detection quality, with a strong emphasis on translating research into production-ready solutions. | Post-trainData | 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 |