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 |
| 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 |
| 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 |
| 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 |
| Senior Researcher - Efficient AI Senior Researcher focused on advancing efficiency across the AI stack for generative AI serving systems, spanning models, ML frameworks, cloud infrastructure, and hardware. The role involves algorithmic and systems optimization for latency, throughput, and cost, with a strong emphasis on driving research ideas through prototyping, validation, and production deployment. | ServePost-train | 8 |
| Senior Researcher - GPU Performance Applied Research role focused on hardware/software codesign for GPU kernel optimizations to improve efficiency of Large Language Models and Generative AI inference. Involves designing, implementing, and optimizing GPU kernels, researching novel optimization techniques, and profiling performance. | 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 |
| Research Intern - Systems For Efficient AI Research intern focused on optimizing AI inference systems, including LLM inference, KV caching, request scheduling, and GPU orchestration, to improve latency, throughput, and cost-efficiency. | 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 |
| Research Intern - AI Systems and Tools Research Intern role focused on developing AI systems and tools, particularly developer tools for Microsoft's custom Maia AI hardware. This involves working on profilers, debuggers, performance analysis tools, and simulators to enable efficient execution of AI models on AI accelerators. The role collaborates with AI researchers, hardware teams, and AI compilers teams, and involves work on device firmware, host software, and integration with AI/ML frameworks. | Serve | 7 |
| Research Intern - AI System Architecture Modeling and Performance Research Intern role focused on AI system architecture modeling and performance within Azure's hyperscale infrastructure. The intern will evaluate hardware/software co-design opportunities, optimize CPU, GPU, and networking infrastructure for AI accelerators, and develop methodologies for performance analysis and architectural idea evaluation. | Serve | 7 |
| Research Intern - AI Hardware Research Intern role focused on AI Hardware, specifically on chip architectures for efficient AI serving and inference systems. The role involves research, analysis, documentation, and innovation in collaboration with researchers and engineers. | Serve | 7 |
| Research Intern - AI Frameworks (Network Systems and Tools) Research intern focused on next-generation AI systems, specifically exploring disaggregated inference, memory-architecture, and interconnect technologies for LLM serving, with a focus on request scheduling and KV caching optimizations. The role involves investigating and evaluating disaggregated KV cache architectures and building a P2P service KV cache sharing architecture. | 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 - Hardware/Software Codesign Research intern focused on advancing the efficiency of AI systems through hardware/software codesign, exploring novel designs and optimizations across the AI stack, including models, frameworks, cloud infrastructure, and hardware. The role involves practical implementation skills for efficient, scalable computational kernels and aims to contribute to mid- and long-term product innovations. | 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 |