Senior Researcher focused on the foundations of generative AI, including new architectures, representations, and learning objectives for foundation models and learning agent platforms. Research areas include proactive agents, test time training, active visual reasoning, world models, multi-scale temporal reasoning, continual learning, multimodal models (VLM, VLA), and real-time agents.

Research Intern position at Microsoft Research Montreal focusing on advancing LLM research in reasoning, interaction (RL training), and modularity, specifically for agentic coding LLMs. The role involves developing, improving, and exploring AI model capabilities, contributing to cutting-edge technologies, and potentially publishing research.

This is an internship opportunity for a Research Scientist at Microsoft, focusing on advancing the state-of-the-art in computer science and engineering through research in areas like Machine Learning, Natural Language Understanding, and Computer Vision. The role involves conducting research, implementing prototypes, and collaborating with teams to push forward research agendas, with a strong emphasis on academic experience and deep thinking.

The Principal Product Manager, Foundational AI Research role at Microsoft AI focuses on advancing the next generation of LLM models. Responsibilities include working on pre-training/post-training data and evaluations, training infrastructure, or API/Platform. The role involves prioritizing research based on customer needs, building evaluations and datasets, and collaborating with AI researchers to execute project plans. Experience in building data collection or evaluation pipelines for AI models and collaborating with ML researchers/engineers is required.

Research role focused on pushing the boundaries of agentic AI, large language, and multimodal models. The role involves developing cutting-edge training methodologies, curating datasets, designing evaluation frameworks, and prototyping new agentic capabilities. Emphasis on research, publication, and potential for real-world impact.

The AI Core Infrastructure team is responsible for building and managing the large-scale GPU management infrastructure and inference/training platforms that power Microsoft's AI workloads. This role focuses on the training infrastructure for large-scale model pre-training, post-training, and fine-tuning on advanced GPUs in Azure and partner clouds.

Principal 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 integrating AI systems, developing research prototypes, and publishing findings in top-tier venues.

This role focuses on building and scaling the high-performance computing (HPC) infrastructure required for training frontier AI models and powering AI products like Copilot. The engineer will design, operate, and maintain large-scale HPC environments, including schedulers and core domains like GPU compute, storage, and networking. Responsibilities include developing automation tools, supporting researchers and engineers, and troubleshooting cluster issues to ensure efficient job scheduling and performance.

Senior Researcher at Microsoft Research focusing on Artificial Specialized Intelligence, developing cutting-edge large foundation models and post-training techniques for specific domains and real-world applications. The role involves conducting research, collaborating with cross-functional teams, developing prototypes, and publishing findings.

Microsoft AI is seeking individuals to train the world's most capable AI frontier models, focusing on scale, performance, and product deployment. The role involves developing algorithms, model architectures, and data mixtures for large-scale training, driving implementations, conducting experiments, and collaborating with infrastructure, data, post-training, and multimodality teams.

Research Intern role focused on advancing Generative AI and Large Language Model Technologies, contributing to the development and exploration of LLMs and Multimodal AI models. The lab's mission is to expand AI capabilities, efficiency, and safety through innovations in foundation models and learning agent platforms, with research areas including reasoning, new architectures, action models, multi-agent systems, and evaluation.

Research role focused on developing and training world-class multimodal AI frontier models, pushing boundaries of scale and performance. Involves algorithm development, model architecture design, experimentation, data innovation, and improving training/deployment efficiency. Collaborates with infrastructure, data engineering, pre-training, post-training, and product feedback teams. Requires strong publication track record and expertise in multimodal research.

Research role focused on training frontier multimodal AI foundation models at scale, pushing boundaries of performance and deployment. Involves algorithm development, model architecture design, experimentation, data innovation, and improving training/deployment efficiency.

Research Intern position focused on the intersection of Machine Learning, Optimization, and Large Language Models (LLMs) for efficient decision-making. Projects involve training LLMs for algorithm design, accelerating optimization algorithms, and using LLMs for sequential decision-making. The role involves designing algorithms/models, prototyping, conducting experiments, and potentially contributing to publications.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Researcher at Microsoft Research Asia (MSRA) in Singapore focusing on Foundation Model innovations (LLM, vision, multi-modality), Deep Learning and Reinforcement Learning Foundation, and Industrial AI applications like Healthcare and Embodied AI/Robotics. Conducts research to advance state-of-the-art, formulates research problems, and initiates research agendas. Bridges research and development, potentially creating long-term business opportunities, but not responsible for immediate product needs.

Researcher at Microsoft focusing on advancing the state-of-the-art in AI, Computer Systems, Networking, NLU, Computer Vision, and ML. The role involves conducting research, leading collaborations, formulating research problems, and developing prototypes. While expertise is provided to product groups, the primary focus is on academic knowledge advancement rather than immediate product needs. The role requires strong programming skills, depth of knowledge in AI fields, and experience in research execution and publication.

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.

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.

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.

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.

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.

Software Engineer role focused on building and managing large-scale GPU infrastructure and training/inference platforms for AI models (LLMs, SLMs, multimodal, code-specific) on Azure and partner clouds. Responsibilities include architecting, designing, and developing core AI infrastructure services, collaborating with researchers, and enhancing system stability, latency, security, and maintainability for training runs.

This role focuses on building and optimizing the compute orchestration and scheduling layer for large-scale AI model pretraining, utilizing Kubernetes and Ray. It involves workload placement, scaling, reliability, and developer experience, with a direct impact on AI model development and deployment infrastructure.

Research Intern position at Microsoft's Office of the Chief Scientific Officer, focusing on strategy and opportunities at the frontiers of science, engineering, and responsible AI. The role involves collaborating with world-class researchers on complex challenges in diverse fields, including AI, biology, biomedicine, and the societal influences of AI. Interns will contribute to research and development strides, present findings, and potentially publish peer-reviewed work.

Senior Researcher in Cloud and AI Infrastructure at Microsoft Research, focusing on advancing AI infrastructure architecture and chip design using AI technologies. The role involves investigating hardware trends, optimizing components, conducting simulations, developing prototypes, and collaborating with cross-functional teams to solve complex real-world challenges at the intersection of AI, human interaction, and environmental context.