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.

Research intern role focused on advancing agentic model capabilities, including reasoning, tool use, and end-to-end workflow execution across text and visual environments. The role involves research in reinforcement learning, novel training algorithms, synthetic environment creation, multi-agent training, and scaling laws, with a focus on foundational models and various data modalities. The internship aims to contribute to cutting-edge research and potentially ship AI technologies in products.

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 position focused on building reliable, safe, and efficient AI agents. The role involves exploring formal verification, reliability, safety, intelligent task handling, secure execution, and efficiency optimization for AI agents. It is a research-focused role within Microsoft Research, aiming to tackle complex challenges in AI agent systems.

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 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.

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.

This role focuses on researching and developing machine learning models, specifically large language models (LLMs), for Microsoft 365 Copilot. The core responsibilities involve advancing research through projects, developing new algorithms and prototypes, and collaborating with product groups and Microsoft Research. The role emphasizes fine-tuning models for specific applications and contributing to the AI platform infrastructure that enables Copilot workflows. The position requires expertise in LLMs, deep learning, and responsible AI, with a strong emphasis on shipping applied research to production.

AI Security Research Intern focused on developing autonomous systems to detect and disrupt cyber attacks in near real-time, leveraging LLMs and agentic frameworks.

Applied Scientist II role at Microsoft focusing on integrating AI research into productivity products like M365 Copilot. The role involves defining and leading research projects, collaborating with cross-functional teams, and contributing to the scientific community through publications. Research areas include reinforcement learning, agentic systems, multimodal modeling, post-training techniques, and LLM applications.

Principal Applied Scientist role at Microsoft AI Web Data team, focusing on building the data foundation for Bing and Microsoft AI experiences. This involves large-scale grounding, LLM training, and end-to-end processing of web content. The role translates research into production, advancing state-of-the-art modeling and deploying algorithms to improve system performance and accuracy.

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.

Research intern position focused on computer vision and deep learning to improve user understanding of devices and environments. Involves analyzing multimodal sensor data and human-object interactions to enhance human-computer interactions, with opportunities to advance the state of the art.

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.

Research intern position focused on LLM safety and security, involving research into protecting LLMs from malicious inputs and using LLMs for computer security. The role involves collaboration with researchers and contributing to research publications.

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.

Research intern to study LLM-based assistants' behavior with incomplete information, focusing on uncertainty awareness, responsible reasoning, and robustness for enterprise AI systems.

Applied Researcher role focused on post-training code specific models and agentic research for developer tools like Github Copilot. The role involves building and managing ML experiments, creating datasets, and collaborating with product teams to apply and advance LLM approaches for software engineering, including RAG and evaluation, with opportunities to ship AI advancements to millions of developers.

Senior Research Scientist to lead cutting-edge projects from concept to product, focusing on AI for Developers. This role involves building and training state-of-the-art models, applying and advancing techniques for leveraging LLMs in software engineering (including RAG and evaluation), and collaborating with product teams to run large-scale experiments and improve AI solutions. The primary focus is on AI for code completion and editing, retrieval-augmented systems for codebases, and efficient inference algorithms for code generation.

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.

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.

Research Intern role focused on agentic programming, involving building agentic workflows and ML models for software engineering tasks, within a PhD program context.

Senior Researcher at Microsoft Research focusing on the intersection of AI systems and society, with an emphasis on sociotechnical approaches to AI evaluation, responsible AI in industry, and AI safety. The role involves interdisciplinary research, collaboration with industry teams, and a strong publication record.

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.

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.

Research role focused on developing and industrializing novel speech algorithms, including integrating speech with LLMs for multimodal modeling, and applying these models to real products with continuous monitoring and evaluation.

Research Intern role focused on advancing the quality, reliability, and evaluation of LLM-based systems by exploring new ML methods for AI assessment and alignment. Responsibilities include co-developing research projects, implementing ML approaches (training/fine-tuning), and developing evaluation frameworks. Requires PhD enrollment in a technical field and hands-on LLM experience.

Research intern to conduct threat modeling for LLM-enabled agentic designs, develop formal security frameworks, and produce security proofs and empirical validations. Deliverable within 12 weeks.

Research intern role at Microsoft Teams focusing on AI-driven innovation in collaboration and communication technologies. Projects may involve AI agents, conversation intelligence, meeting efficiency, and user experience, with a strong emphasis on privacy, security, and accessibility. The role involves applying research methods to real-world challenges in digital collaboration.

Seeking Data Research Engineers to join the Multimodal team, focusing on designing and curating high-quality datasets for next-generation foundation models across vision, language, and audio. The role involves developing data collection strategies, improving dataset quality, analyzing data-driven model behaviors, and building tools for dataset auditing, all within the context of responsible AI practices.

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.

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.

Research Intern position at Microsoft's Sociotechnical Alignment Center (STAC) focusing on evaluating AI systems, particularly generative ones. The role involves applying measurement theory from social sciences and statistics to assess risks, capabilities, and performance. Collaboration with Fairness, Accountability, Transparency, and Ethics in AI (FATE) researchers is expected. The internship emphasizes theoretical and methodological approaches to advance AI system evaluation.

Research intern focused on accelerating large language models (LLMs) by optimizing performance on custom architectures, involving computer architecture and parallel programming.

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.

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.

Research Intern position at Microsoft Health Futures focusing on applying ML and statistical modeling to understand the human immune system for precision medicine. The role involves building large-scale models of immune responses and immune cells, integrating techniques like representation learning, causal inference, and generative modeling with biological insights.

Research Intern position focused on applying machine learning techniques to biology and healthcare problems, including generative models, computational immunology, and statistical genetics.

Principal Security Researcher focused on designing and executing advanced adversary simulations using AI-enabled and agentic systems. The role involves evaluating AI-driven detections and defenses, translating attacker tradecraft into actionable insights, and contributing to the development of AI-driven security research workflows.

Principal Security Researcher (Red Team) at Microsoft, focused on using AI and agentic systems to scale offensive security research, adversary emulation, and tooling development. The role involves designing and executing complex attack simulations, developing advanced offensive tools, and evaluating defensive systems, with a strong emphasis on AI-enabled automation and adaptive attack paths.

Senior Security Researcher role focused on offensive security research using AI-enabled and agentic systems to emulate real-world cyberattacks. The role involves designing and executing adversary simulations, developing offensive tooling, conducting malware research, and leveraging threat intelligence. A key aspect is utilizing AI and LLM-driven workflows to scale attack development, automation, and simulation fidelity, while partnering with blue teams to improve detections and defensive capabilities.

Principal Research Manager to lead AI research strategy and execution for Microsoft's Commercial Engineering & AI (CEAI) division, focusing on transforming commercial business with AI-native engineering and intelligent systems. The role involves managing a research team, driving AI UX innovation, and ensuring research directly informs product development and delivers measurable impact for users and the business.

Research Intern role focused on exploring the intersection of quantum applications and quantum system architecture using AI-driven methods and machine learning for advanced resource estimation. The goal is to co-design more efficient quantum systems aligned with real-world application workloads, from application intent to hardware realization.

Security Research Intern role focused on analyzing real-world nation state attacks to develop autonomous detection and disruption logic using AI-assisted tooling and agentic flows. The role involves investigating threats, reasoning over large-scale datasets, and contributing to the implementation of automated capabilities to protect users.

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.

PhD Intern role focused on applying advanced machine learning concepts and data analysis to real-world problems, developing prototypes, and contributing to research in machine intelligence.