Jobs at Microsoft

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.

Develop machine learning techniques focused on AI safety, alignment, and trustworthiness. Collaborate with product, research, and engineering teams to design, build, deploy, monitor, and iterate responsible AI systems at scale, from experimentation to production for large language models and distributed AI services.

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 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.

Lead customer-facing data science engagements: manage data acquisition and cleaning, build and evaluate scalable models, drive model best practices and ethics, write extensible code, research industry trends, define solution strategy, and collaborate across engineering and product teams to deliver AI/cloud solutions.

Design, implement, test, and optimize components of AI/ML frameworks (ONNX, ONNX Runtime, Foundry Local). Improve system performance and efficiency, collaborate with internal/external partners, provide technical support, and contribute to open-source and cross-platform deployments for devices from servers to mobile and edge.

Lead cross-functional engineering programs that build cloud and AI solutions with customers. Define success criteria, coordinate roadmaps, track schedules, drive staging/implementation, validate use cases, write test cases, and lead governance and customer engagements.

Drive complex, cross-functional engineering projects as a Product Owner: define customer scenarios, coordinate engineering and stakeholders, deliver roadmaps, track schedules, validate use cases, write test cases, collect metrics, lead governance and customer engagements to implement cloud and AI-based solutions.

Design and build scalable AI-first experimentation and growth systems: telemetry, experiment assignment, feature flighting, rollout automation, and risk controls. Lead cross-team initiatives, partner with Product/Data Science/Design, write production code, review implementations, and raise engineering and experimentation quality across products.

Build and ship AI-first growth experiments and scalable systems to drive acquisition, activation, engagement, and retention. Design and evolve A/B testing frameworks, instrumentation, metrics, and tooling; partner with Product, Data Science, Design, and Research to iterate quickly and scale successful patterns across global, high-traffic AI products.

Lead end-to-end segmentation strategy for Microsoft Advertising, translating business priorities into coverage, capacity, and resource-allocation models. Build measurement frameworks, analytical models, and cross-functional alignment to operationalize segmentation into territory design, quota and capacity planning. Advise senior leaders and continuously refine models using data-driven insights to drive growth.

Lead a global technical sales organization for Microsoft Channel partners to drive partner transformation to AI-first, services-led businesses. Coach and manage cross-solution partner architects, set technical strategy across Copilot, Agents, Azure and Security, orchestrate executive engagement, ensure solution quality and operational readiness, drive partner-led consumption and pipeline discipline, surface partner insights, and build scalable IP and enablement models to accelerate customer adoption and partner profitability.

Generate actionable insights for Microsoft Advertising by integrating and analyzing large datasets, applying statistical methods, ensuring data governance, collaborating with internal and client teams, and presenting persuasive visualizations and narratives to influence senior stakeholders and drive ad investment decisions.

Lead design of scalable regulatory, governance, and compliance frameworks for advertising; partner across product, engineering, legal, trust & safety, and ops; identify emerging regulatory risks; drive cross-organizational programs balancing customer experience and risk; create intake, prioritization, and readiness processes; produce executive narratives and strategic roadmaps; advise senior stakeholders and build global partnerships to ensure scalable, compliant solutions.

Design, train, and evaluate Responsible AI components: fine-tune LLMs (including RLHF), build adversarial agent evaluations and safety mitigations, collaborate with engineering to deploy mitigations at scale, monitor operational performance, and troubleshoot end-to-end issues.

Lead customer-facing data science engagements: acquire and prepare data, evaluate and operationalize models at scale, drive modeling best practices, research industry trends, write extensible code, and define solution and customer strategy while promoting ethics and privacy.

Lead software architecture and performance optimization for AI accelerator platforms across kernels, compiler/runtime, distributed training and inference. Prototype and validate software, analyze large-scale workload behavior to find bottlenecks and numerical correctness issues, and guide hardware-software co-design and production-scale system tradeoffs with cross-functional teams.

Lead design and delivery of cloud-based solutions, collaborate with customers and product teams, produce extensible code, mentor engineers, own design documents and dependencies, act as a designated responsible individual (DRI) including on-call system monitoring, and improve reliability, performance, and observability at scale.

Work with customers and cross-functional teams to design, build, and deliver cloud-based solutions. Develop, optimize, debug, and refactor code; produce design docs; act as DRI and on-call responder; improve system reliability, observability, and performance; contribute to open-source and collaborate with Microsoft product teams.

Work with customers and cross-functional teams to design, implement, and deliver cloud-based software solutions. Write and reuse code, create design documents, break down work, act as on-call DRI for simple incidents, and stay current with technologies. Contribute to open-source and collaborate with product teams to build scalable, observable systems.