Seeking engineers and researchers to join the Pretraining Text Data team to build the next generation of foundation large language models. The role focuses on designing and curating high-quality datasets, developing novel data collection strategies, improving dataset quality and integrity, understanding data-driven model behaviors, training models on data impact, and aligning datasets with ethical and societal values. This is a cross-disciplinary, high-impact role at the intersection of data and innovation.

Seeking engineers and researchers to join the Pretraining Text Data team to build the next generation of foundation large language models. The role involves designing and curating high-quality text datasets, developing novel data collection strategies, improving dataset quality, understanding data-driven model behaviors, and aligning datasets with ethical values. Responsibilities include creating datasets for training and evaluation, developing scalable data pipelines, analyzing datasets, building tools for auditing, and collaborating with safety and ethics teams.

The AI Data team at Microsoft AI is building the world's most advanced multimodal dataset to power frontier AI models. This role focuses on designing and developing data pipelines for massive multi-modal training data (text, audio, images, video) and building infrastructure to store and process petabytes of data. The team partners with pre-training and post-training teams to improve data recipes through experimentation and collaborates with product teams to identify model gaps.

This Principal Product Manager role within Microsoft AI focuses on defining the vision, strategy, and execution for AI training pipelines. The role involves leading cross-functional teams to build scalable and high-quality training data collection and processing systems, defining success metrics, and ensuring compliance. It requires deep collaboration with engineering, research, and data science to operationalize new evaluation techniques and metrics for LLM and ML-based products, with a strong emphasis on data processing, infrastructure, and evaluation systems.

This role focuses on building and optimizing training data pipelines and evaluation frameworks for audio models, with a secondary focus on model tuning and deployment. The engineer will be responsible for data sourcing, cleaning, labeling, QA, versioning, and lineage, as well as developing evaluation frameworks and driving continuous quality improvements. They will also optimize training and inference performance for latency, throughput, cost, and reliability.

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.

Principal AI Software Architect role focused on enabling and optimizing machine learning model training workflows on custom hardware (MAIA accelerators). Requires expertise in PyTorch, Triton/CUDA, and understanding of accelerator architecture for efficient deployment of large models.

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, GPU compute, storage, and networking. Responsibilities include developing automation, supporting researchers and engineers, and troubleshooting cluster issues. The role requires experience with on-premise or cloud HPC clusters, high-scale training clusters, and public cloud infrastructure.

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 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.

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.

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.

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.

Principal Machine Learning Engineer to work on data labeling and classification for large-scale multimodal Copilot data within Microsoft AI. The role involves prototyping and productionizing classification flows, operating prompted classifiers, and building secure data-labeling pipelines. Requires experience in data pipelines, data science, ML, and strong communication skills.

Microsoft AI is seeking an experienced Data Engineer to build mission-critical data pipelines for their Copilot systems. The role involves ingesting, processing, and publishing data streams to support AI model fine-tuning and introspection. The ideal candidate will have strong big data processing skills and experience with cloud infrastructure.

This role is for a Data Engineering Manager within Microsoft AI's Copilot team. The primary responsibility is to build and manage scalable data pipelines that ingest, process, and publish data streams for AI use cases, specifically for fine-tuning models and improving human-AI interactions. The role involves managing a team of data engineers and ensuring operational excellence for the data platform.

This role focuses on building and architecting distributed data platforms and pipelines that process massive datasets for AI models, including training, inference, and evaluation. It involves designing event-driven architectures, handling unstructured data, engineering feedback loops for AI, and optimizing compute for cost and performance.

Backend Engineer role focused on building the data foundations for Copilot's memory and personalization features. This involves designing and operating large-scale data pipelines for signal ingestion, normalization, enrichment, aggregation, and memory generation, enabling downstream ML and product consumers. The role also involves technical leadership in data systems and influencing architecture.

This role focuses on researching and developing next-generation intrusion detection systems by leveraging large-scale security event logs and applying advanced data processing and machine learning techniques. The goal is to achieve accurate and rapid detection of sophisticated attacks.

Research intern to work on multi-modal sensing, device security, and authentication, with opportunities to influence next-generation device design. The role involves prototyping on mobile OS, Android development, and performing preliminary user evaluations. Familiarity with speech interfaces to agents and LLMs is a plus.

The AI Data Infra team at Microsoft AI is responsible for building data infrastructure to help MAI teams to generate the biggest and best training dataset. This role focuses on designing and developing data pipelines for multimodal training data and owning critical data infrastructures like Spark, Ray, and Vector Databases.

Seeking Data Research Engineers to join the Multimodal team, focusing on building next-generation foundation models. The role involves exploring, designing, and building high-quality multimodal datasets (vision, language, audio) for training and evaluation, collaborating with scientists and engineers, and developing scalable data pipelines. Responsibilities include data analysis, quality assessment, building tools for auditing, and ensuring datasets meet responsible AI practices.

The role focuses on building and maintaining data infrastructure for large-scale AI model training, specifically ingesting and processing enormous amounts of multimodal data (text, audio, images, video). This includes owning data pipelines, Spark, Ray, and Vector Databases, and partnering with pretraining and post-training teams to improve the data recipe for frontier models.

Research Intern position focused on applying AI to enhance medical image reconstruction techniques for MRI and CT scanners, aiming to improve image acquisition speed and diagnostic quality. The role involves working at the intersection of MRI physics, signal processing, image reconstruction, and AI within the Microsoft Health Futures team.

Research Intern role in the RiSE group focusing on ML Systems, AI workloads, agentic workflows, and ML models for software engineering tasks. Requires PhD program enrollment and expertise in related STEM fields, with preferred qualifications in ML systems, AI, and software engineering.

The Principal Data Scientist will leverage data science techniques to solve real-life problems, focusing on defining compensable metrics, designing quota models, and evaluating outcomes. The role involves partnering with data engineering, product, field, and Finance teams to turn large-scale telemetry into decision-ready insights, influencing product direction and executive decision-making. Responsibilities include defining quota-setting strategy, applying ML to quota and incentive design, bridging Finance and Sales teams, and educating stakeholders on quota methodology. The role also involves analyzing challenges, shaping strategy, writing efficient code, leading data integration, and applying expert-level proficiency in big-data and ML engineering tools. Additionally, the role emphasizes a customer-first mindset, building data platforms, and incorporating AI ethics best practices.

Consultant role focused on delivering end-to-end data and AI solutions using Microsoft technologies. Responsibilities include solution design, development, deployment, and ensuring customer value through technical expertise and customer focus. The role involves working with Azure Data Services, AI/ML foundations, and operationalizing ML pipelines.

Senior Consultant Data & AI at Microsoft, focusing on delivering end-to-end data and AI solutions for clients. Responsibilities include designing, developing, and deploying solutions on Microsoft technologies, building AI-powered data pipelines, feature engineering, operationalizing ML pipelines, and working with LLMs, NLP, Computer Vision, RAG, and Gen AI frameworks. The role emphasizes Azure Data Services, Data Warehouse, and MLOps concepts.

Consultant role focused on delivering end-to-end data and AI solutions using Microsoft technologies. The role involves designing, developing, and deploying solutions, with a focus on data engineering, ML-ready datasets, and operationalizing ML pipelines on Azure. It requires strong foundational knowledge of Azure Data Services, AI/ML concepts, and experience with AI-powered data pipelines.

This Principal Data Scientist role focuses on leveraging AI tools to accelerate workflows and amplify team productivity within Microsoft's CoreAI Growth and Data Science team. The role involves delivering insights, reporting, models, and tools to guide product strategy and drive growth across the developer ecosystem. Key responsibilities include providing critical analyses to executives, driving alignment across stakeholders, identifying high ROI data opportunities, contributing to data insight scaling infrastructure and culture, mentoring, and operationalizing models and reporting. While the role uses AI tools, its primary focus is on data science and analytics to support product strategy and growth, rather than building core AI models.

Data Engineer role focused on building and operating data ingestion, transformation, and validation pipelines that power experimentation, insights, and AI features for SwiftKey. The role involves working with large-scale data systems in cloud environments, ensuring data quality, and supporting AI feature development.

This Principal Software Engineer role focuses on building and operating large-scale, real-time data pipelines and feature/embedding materialization systems for Microsoft Ads. The role involves designing and implementing streaming ETL, managing messaging systems like Kafka, ensuring data contracts, and integrating with ML inference serving. Success metrics include freshness, correctness, latency, reliability, and cost. The role requires strong programming skills, experience with distributed systems, and observability.

Senior Data Scientist role within Microsoft's Industry Solutions Engineering (ISE) team, focusing on developing AI and cloud-based solutions for customers. The role involves data acquisition, dataset development, model evaluation, and building operational models at scale, working collaboratively with customers and internal product teams.

Software Engineer on a data engineering team that builds and manages large-scale, real-time data platforms and analytics systems. The role focuses on transforming raw signals into trusted, high-quality data products used for automation, decision-making, and AI-driven workflows, enabling agentic automation for infrastructure services. The team uses modern data mesh architectures and emphasizes reliability, governance, and observability.

This role focuses on designing and implementing large-scale data pipelines and models for an AI infrastructure platform, processing terabytes to petabytes of data daily. The engineer will ensure data correctness, reliability, and usability for experimentation and analytics, working closely with data scientists and platform engineers.

Software Engineer II on the Microsoft Fabric Data & Telemetry team, responsible for building and maintaining telemetry instrumentation services and pipelines, developing tools for metadata management, and creating job monitoring and notification services for data pipelines. The role focuses on providing high-quality data for running the service and business, supporting pillars like live-site monitoring, diagnostics, and analytics for product development, and ensuring customers have data for their own observability needs. The team applies classic cloud and software engineering practices alongside big data-engineering and analytical practices.

Senior Software Engineer role at Microsoft Azure Data engineering team, focusing on designing and building internal tools, engineering systems, and automation capabilities to enhance the quality and reliability of Power BI Desktop and Service. The role involves end-to-end tool development, including architecture, backend services, dashboards, telemetry integration, and AI-powered workflows, with a focus on integrating GenAI into developer workflows and modernizing engineering processes.

Senior Researcher in Data Systems at Microsoft Research focusing on query execution, data storage, resource management, data discovery, and data preparation. Special interest in leveraging AI/ML for data management challenges. Past research has influenced products like SQL Server and Azure SQL Database. Requires a Doctorate or equivalent experience and a track record of research accomplishments, including major conference publications.

This is a Research Intern position within Microsoft's Office of the Chief Scientific Officer, focusing on strategy and opportunities at the frontiers of science, engineering, and responsible AI. The intern will collaborate with researchers on various projects, contributing to research and development strides in areas like AI, biology, and responsible AI, with a focus on societal influences.

Research intern focused on data systems, with potential to leverage AI/ML for data management challenges. The role involves working with researchers on innovative solutions and contributing to publications.