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.

This role focuses on building and improving AI agent platforms, specifically the Agent Performance team within Azure AI Platform. The core responsibility is to integrate scientific advancements, particularly RL techniques like RLHF, into production-ready features for AI agents. The role involves monitoring, evaluating, optimizing, and enabling self-improvement of these agents, bridging the gap between research and product.

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 Software Engineer at Microsoft Quantum focused on building system software for quantum computers, integrating AI, and developing novel algorithms for computationally hard problems. The role involves designing, implementing, and optimizing software and firmware subsystems for quantum hardware, with a focus on quantum error correction and real-time quantum stacks.

Senior Software Engineer role focused on optimizing large language model (LLM) deployment on Microsoft's MAIA AI accelerators and GPUs. The role involves building software across the stack, including PyTorch, inference systems (vLLM, SGLang), and performance-critical runtime/kernel components. Responsibilities include architecting tensor computation primitives, extending PyTorch for custom accelerators, improving inference stacks, and optimizing kernels for LLM inference and training workloads.

Principal Product Manager for Microsoft Dynamics 365 Contact Center, focusing on AI-led voice capabilities. The role involves owning the strategy, vision, and roadmap for AI-powered voice experiences, including cloud telephony, IVR, real-time voice AI, and post-call analytics. It requires collaboration with various Microsoft teams, engagement with strategic customers, and driving go-to-market readiness. The role also involves mentoring other PMs and representing Microsoft externally in the CCaaS and contact center AI space.

The Signals Modeling team builds core intelligence for predicting user interaction with ads, designing and training large-scale transformer models for ad ranking, pricing, and optimization. They own end-to-end ML systems, from data construction to deploying models that drive revenue and ROI in a massive ads ecosystem.

Full Stack Engineer to build LLM-powered data engineering experiences and infrastructure for Microsoft Fabric. The role involves implementing agentic workflows and scalable LLM-backed data features, focusing on AI Engineering and modern LLM-based systems.

Senior Director role focused on leading a team to drive AI adoption within healthcare environments, translating AI capabilities into scalable, real-world use cases and operationalized solutions. This involves people management, customer advocacy, and ensuring solutions align with business goals and company methodologies.

This role focuses on building and scaling Azure's next-generation Model Router, which involves optimizing and deploying LLMs at a global scale. The responsibilities include applying advanced concepts to product needs, working with large-scale computing frameworks for model improvement, deploying and evaluating models in production, and monitoring their performance over time. The role also involves collaboration with product groups, mentorship, and documentation.

Senior Software Engineer role in Microsoft's CoreAI division, focusing on building AI-powered developer tools and planet-scale platforms with enterprise trust, security, and reliability. The role involves designing, building, and operating core platform services for developers across the entire application lifecycle, including AI-native engineering practices and AI-enabled systems to improve various aspects of the software development lifecycle.

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.

Software Engineer II role focused on building foundational platforms for intelligent agents and generative AI systems within Microsoft Foundry. The role involves developing large-scale, cloud-native systems for the end-to-end agent lifecycle, including secure enterprise deployment, tool integration, model fine-tuning, and production observability/evaluation. It sits at the intersection of distributed systems, AI infrastructure, and developer platforms.

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.

Senior Software Engineer on the AI Frameworks team at Microsoft, focusing on developing AI software that enables running AI models across various devices and hardware. The role involves hands-on software design and development in C/C++ for large-scale model training and inference on novel AI hardware, requiring a strong engineering background and the ability to solve complex technical problems.

This role focuses on delivering enterprise AI solutions using Azure OpenAI, Azure AI Services, and custom machine learning. It involves designing and implementing secure, advanced agentic AI systems and optimized RAG architectures, requiring expertise in full-stack application engineering, cloud-native architecture on Azure, and DevOps. The role also emphasizes solutioning, pre-sales, and technical leadership, with a requirement for relevant Azure AI certifications.

Senior Consultant role focused on designing and delivering end-to-end, industry-aligned, AI-powered cloud-native applications for enterprise customers. Combines full-stack engineering, applied AI, and Azure cloud expertise with a consulting mindset to drive business outcomes and digital transformation.

Principal Software Engineer in the CoreAI organization at Microsoft, focusing on building and integrating Responsible AI services. The role involves developing customer-facing, high-performance, low-latency, and high-availability AI services, improving AI tools across the SDLC, and ensuring Responsible AI controls and engineering-health metrics are embedded. Responsibilities include coding, system design, driving engineering excellence, implementing AI features with guardrails, and ensuring reliability and supportability.

Principal Data Scientist role within Microsoft's Industry Solutions Engineering (ISE) team, focusing on developing AI-powered cloud solutions for customers. The role involves data acquisition, model evaluation, research, and strategy definition, with a strong emphasis on customer collaboration and delivering impactful, scalable solutions.

Principal Software Engineer to lead architecture and delivery of a Teams-integrated product (Innovation Studio) that uses agentic AI workflows, Azure-native services, and modern web experiences to help organizations run hackathons and accelerate ideas. The role involves defining how the team uses agentic development itself for various SDLC stages.

The Applied Scientist II will design, develop, and ship AI models into the Teams media stack, focusing on real-time conversation products like Teams. This role involves building end-to-end ML systems, from data cleaning and feature engineering to model training, evaluation, and deployment, with an emphasis on optimizing for performance and memory, and updating deployed models based on A/B testing.

Senior Software Engineer on the Bing Multimedia team, focusing on AI-powered visual discovery and multimodal experiences. The role involves designing and building large-scale AI systems, integrating LLMs and multimodal AI into production, and contributing to both backend services and user-facing components for Bing Image Search and other Microsoft AI products.

The Principal Software Engineer - Performance Tooling role focuses on optimizing the performance of AI models, particularly LLMs, across various hardware platforms (GPUs, CPUs) and software layers. This involves benchmarking, debugging, profiling, and optimizing for large-scale training and inference to reduce deployment time and hardware footprint, contributing to the efficiency of AI services like Azure OpenAI.

This role focuses on building and extending AI-driven agents for incident triage, classification, and automation within Microsoft's Azure Data engineering team. The goal is to replace manual operations with engineered solutions, improving the stability and efficiency of cloud-scale data infrastructure.

This role focuses on architecting and designing AI solutions, specifically leveraging Microsoft's Copilot and agent technologies, to address customer business challenges. The architect will assess customer AI readiness, translate business requirements into technical solutions using Power Platform, Azure, and Microsoft 365 Copilot, and ensure scalable, secure, and compliant deployments. The role involves close collaboration with customers, product engineering, and delivery teams to drive adoption and validate business value.

This role focuses on co-engineering Generative AI and agentic solutions for enterprise customers on Microsoft platforms. The consultant will translate ambiguous business needs into requirements, design and implement GenAI/agentic solutions, prototype rapidly, and ensure production-ready implementations with testing, monitoring, and secure deployment. Key responsibilities include identifying and mitigating AI-specific risks, building agentic workflows with tool invocation and guardrails, and implementing evaluation strategies for AI output quality and safety.

Senior Consultant, AI Business Solutions at Microsoft, focusing on co-engineering GenAI and agentic solutions for customers on Microsoft platforms. The role involves translating ambiguous business needs into working prototypes and production-ready solutions, with an emphasis on end-to-end delivery, risk mitigation, and evaluation of AI outputs. Requires strong engineering and consulting skills to deliver measurable business outcomes.

Forward Deployed Engineer (FDE) role focused on building and deploying AI-powered solutions for customers, working at the intersection of advanced AI technology and real-world business impact. Responsibilities include engineering data pipelines, building custom applications, deploying scalable workflows, and monitoring/refining solutions. Requires practical experience with AI/LLMs in production and leveraging generative AI.

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.

Senior Software Engineer role focused on integrating AI capabilities into traditional computer systems and products across Microsoft's Experiences & Devices division. The role involves formulating design patterns, creating prototypes, architecting solutions, and delivering AI-enabled experiences, with a focus on agent-based systems and AI integration into agent workflows.

Product Manager for the IQ Team (Ontology & Semantic Layer) within Azure Data, focusing on building the semantic backbone that gives AI agents context to reason about business. The role involves defining and delivering the semantic layer vision for Fabric, driving AI-native scenarios by grounding agents in live business operations, and leading end-to-end product strategy and execution for AI solutions on the Fabric platform.

Software Engineer role focused on building an agentic engineering platform for AI-powered productivity across Microsoft's codebases, involving AI models and orchestration frameworks.

Senior Software Engineer role focused on building an agentic engineering platform for Microsoft developers, leveraging AI models and orchestration frameworks to enhance software engineering workflows like code refactoring and understanding. The role involves designing, developing, and deploying platform capabilities, applying AI-assisted development tools, and mentoring other engineers.

This Principal Software Engineer role focuses on building a new AI agent platform for enterprise use within Microsoft Copilot Studio. The role involves designing and delivering scalable, secure, and reliable platform capabilities for autonomous agents that can perform multi-step work, operate across contexts, and integrate with Microsoft 365 and Power Platform tools. The position is at the intersection of distributed systems, applied AI, and user experience, requiring leadership in system design, technical execution, and championing engineering excellence.

Applied Scientist II role on the Bing Places team, focusing on building and shipping AI/ML solutions for local search experiences. The role involves end-to-end work from problem formulation to production deployment, with a focus on LLMs, RAG, learning-to-ranking, and entity understanding. Collaboration with engineering and product partners is key, with opportunities for publications and patents.

Senior Applied Scientist role focused on leveraging LLMs, SLMs, and RAG models to improve the Bing Places platform. The role involves designing, developing, and deploying AI solutions, creating data pipelines, and staying updated on AI/ML research. Collaboration with multidisciplinary teams and mentoring junior members are key aspects.

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.

AI & Cybersecurity Solution Architect responsible for leading AI security pre-sales for complex AI and cybersecurity solutions on Microsoft Cloud, translating client requirements into custom security architectures, and acting as a trusted advisor to CISOs and Chief AI Officers.

This role is for an Azure Apps & AI Cloud Solution Architect (CSA) focused on Federal Government and Defence customers in highly regulated environments. The primary responsibility is to design, enable, and scale modern cloud applications and secure AI solutions on Azure, helping customers move from AI pilots to production and drive Azure consumption and innovation.

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.

Principal Architect role focused on leading enterprise-scale AI adoption and delivery, embedding AI-native principles, and driving intelligent automation and agentic workflows. The role involves acting as a trusted advisor to C-suite executives, shaping technical strategies, and ensuring engineering excellence and compliance in regulated environments.

Product Management Manager role focused on leading a team to define and drive the product roadmap for AI-powered collaboration experiences within the OneDrive and SharePoint organization. The role involves people leadership, product strategy, and cross-functional collaboration, with a strong emphasis on integrating AI/ML technologies like Microsoft Copilot and AI agents into enterprise content management and compliance workflows.