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 |
|---|---|---|
| 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 |
| 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 |
| Cambridge Residency Programme: Next-Generation AI Datacentre Networking Microsoft Research Cambridge is seeking two researchers for a two-year postdoctoral program to advance the design and evaluation of next-generation datacentre networks specifically for AI training and inference workloads. The program involves two tracks: one focused on analytical modeling and simulation, and the other on systems implementation and experimental validation using advanced hardware testbeds. The goal is to publish research findings and influence future AI infrastructure strategy. | Serve | 8 |
| Research Intern - AI/ML Numerics & Efficiency Research Intern role focusing on ML systems, numeric precision, data types, and compute technologies for AI workloads at Azure scale. The role involves investigating model efficiency through low-precision formats, quantization, ML kernel development, and benchmarking. It aims to inform decisions on compute platforms, acceleration strategies, and system-level optimizations for training and inference of large-scale models. | Serve | 8 |
| Research Intern - AI Systems & Architecture Research internship focused on AI systems and architecture, investigating performance modeling, architectural analysis, and emerging inference mechanisms for large-scale AI workloads. The role involves analyzing hardware, software, and model interactions, developing performance models, and prototyping new inference techniques. | Serve | 8 |
| Research Intern - LLM Acceleration Research intern focused on accelerating large language models (LLMs) by optimizing performance on custom architectures, involving computer architecture and parallel programming. | Serve | 8 |
| Principal Researcher - Systems & Networking - Microsoft Research Principal Researcher in Systems and Networking with a focus on AI-driven methods for systems innovation, performance, efficiency, and scalability. The role involves developing new methodologies, collaborating with cross-functional teams, and publishing research findings. | Serve | 7 |
| Principal Researcher - Cloud and AI Infrastructure - Microsoft Research Principal Researcher at Microsoft Research focused on advancing cloud and AI infrastructure architecture, and chip design using AI technologies. The role involves investigating hardware trends, designing and optimizing hardware components, conducting simulations, developing prototypes, and collaborating with cross-functional teams to integrate intelligent systems across computing layers. | Serve | 7 |
| Senior Researcher - Systems and Networking, Microsoft Research Senior Researcher in Systems and Networking at Microsoft Research, focusing on AI-driven methods for system innovation, performance, efficiency, and scalability. The role involves developing and implementing new methodologies, collaborating with cross-functional teams, and publishing research findings. Requires a Doctorate and background in systems/networking with knowledge of ML systems, databases, and networking technologies, including Agent Systems and Vector Databases. | Serve | 7 |
| Research Intern - AI Hardware Research Intern role focused on AI Hardware, specifically researching chip architectures for efficient AI serving and inference systems. Collaborates with researchers to increase performance and efficiency of cutting-edge inference systems. | Serve | 7 |
| Research Intern - Azure Research - Systems Research Intern role focused on next-generation cloud and AI systems, with a focus on improving efficiency, reliability, and usability of Microsoft's online services and datacenters. Projects include efficient GPU/LLM deployments, AIOps, and serverless computing. The role involves research, prototyping, evaluation, and potential publication. | Serve | 7 |
| Research Intern - MSR Software-Hardware Co-design Research intern role focused on pioneering technologies for AI/ML workloads, specifically improving efficiency, security, and robustness of GPU memory systems, agentic AI systems, and software architecture for hardware accelerators. The role involves fast-paced execution, implementation, and evaluation on Azure platforms, with a focus on systems and AI. | Serve | 7 |
| Research Intern - Azure Storage Research intern role focused on optimizing storage systems for AI workloads, including training, checkpointing, and inferencing. The role involves working with leading-edge AI customers to gain insights into their needs. | Serve | 5 |