Jobs at Microsoft

Lead integration of cutting-edge RL and agent self-improvement techniques into the Foundry Agent Platform. Design experiments, evaluate and optimize agent performance, collaborate with researchers and engineers, build actionable observability and visualizations, and mentor team members to drive production-quality AI features.

Lead research on agentic systems, agent ecosystems, advanced agentic capabilities, human-agent interaction, evaluation tooling, and responsible AI. Build and deploy prototypes, collaborate across teams, publish research, and translate innovations into practical, impactful applications.

Build and maintain generative AI and agentic systems: create data, evaluation, and training pipelines; develop models and agent frameworks; prototype end-to-end experiences; collaborate with researchers, engineers, and PMs to translate research into production-ready proofs of concept.

Lead and conduct research on agentic AI, develop training algorithms and datasets for large language and multimodal models, design evaluation frameworks for reasoning and long-horizon tasks, prototype agentic capabilities (action models, memory, multi-agent orchestration), and drive research to publication and production impact in collaboration with engineers and product teams.

Conduct and lead research on agentic AI, developing training methodologies, datasets, and evaluation frameworks for large language and multimodal models. Prototype agentic capabilities (action models, memory, multi-agent orchestration), collaborate with engineering and product teams, and drive research to publication and real-world deployment.

Lead positioning, go-to-market, and launches for Microsoft Foundry Control Plane security and governance features. Partner with product, engineering, security, and sales to craft messaging, enable field teams, manage analyst relations and partners, and measure adoption and campaign performance.

Lead research on agentic AI including recursive self-improvement, multi-agent coordination, continual learning, autonomous skill acquisition, and human-AI collaboration. Build evaluation frameworks and synthetic data pipelines, refine scalable architectures, and drive research-to-deployment in collaboration with engineers and product teams.

Lead research on agentic AI, developing self-improving, multi-agent systems and continual learning methods. Design evaluation frameworks, synthetic data pipelines, and scalable architectures to move research into deployed products while collaborating with engineers and product teams.

Build and maintain cloud-native, large-scale services for deploying, running, fine-tuning, and observing AI agents. Contribute to distributed systems, backend services, tooling, debugging, design discussions, and delivery of production-ready features with strong testing and reliability practices.

12-week in-person research internship at Microsoft Research NYC on self-improving AI systems. Work with mentors and peers on language modeling and reinforcement learning research, present findings, and contribute to projects. Applicants must submit references, a cover letter, and work samples.

Lead applied research projects that move LLM-based code models from research to product: build and train code models, create datasets from public and internal code, run large-scale ML experiments, collaborate with product and engineering teams, and evaluate and iterate AI for developer tools.

Lead and translate AI research into developer products: build datasets from public and internal code, design and run large-scale ML experiments, train state-of-the-art models, collaborate with product teams across Microsoft and GitHub, and evaluate and iterate AI systems for software engineering.

Lead analytics-driven programs to identify global advertising monetization and growth opportunities. Collaborate with Business Planning, Demand Planning, Market Sciences, and Sales Strategy to design demand programs, measure impact, and influence leadership with data-driven recommendations.

Serve as a strategic HR business partner for Cloud + AI, advising leaders, diagnosing organizational effectiveness, driving talent and leadership development, applying data-driven insights and AI-enabled tools, leading strategic projects end-to-end, and delivering scalable HR solutions in partnership with HR centers of excellence and business stakeholders.

Lead design, implementation, and operation of high-performance, real-time auction services on a large-scale distributed advertising platform. Architect and deliver scalable features, optimize performance, run production support, participate in planning, code reviews, and mentor junior engineers.

Lead customer-facing data science engagements: manage data acquisition/cleaning, develop and evaluate scalable models, drive modeling best practices, contribute thought leadership, write extensible code, and define solution and business strategy with cross-functional teams.

Partner with engineering and product leaders to source, engage, and hire technical talent for Cloud + AI (Azure) teams. Develop creative sourcing strategies, drive hiring plans using data and market research, manage stakeholder engagement, ensure strong candidate experience, and maintain compliance and documentation (e.g., OFCCP, GDPR). Coach hiring teams and optimize recruiting processes to meet business and diversity goals.

Lead development of high-scale experimentation platform capabilities, translating research into production features, advancing online experimentation methodology, advising cross-functional teams, and mentoring engineers and scientists to drive trustworthy AI evaluation and measurement.

Design, build, and operate high-scale experimentation platform components for AI systems. Lead architecture, produce reliable, secure, and performant services, mentor engineers, collaborate with PMs and SRE/privacy/security partners, maintain on-call operations, and drive automation, observability, and experimentation best practices.

Design, implement, and maintain scalable experimentation platform services. Collaborate with engineers, PMs, and privacy/security/SRE partners to deliver reliable, diagnosable features, participate in on-call rotations, and improve tooling, telemetry, and automation to support large-scale A/B testing and AI product experimentation.