Jobs at Microsoft

Manage and coach a team of datacenter trainers to design and deliver technical workforce training, assess learning needs, close operational training gaps, partner with site managers, and align training with availability, safety, and throughput goals across global datacenters.

PhD intern will research and prototype AI techniques for Azure SQL Database, analyze algorithms on large datasets, build scalable ML systems, collaborate with researchers and product teams, and contribute to technology transfer and publications.

Work on real-world data science projects using machine learning, statistics, experiments, and data exploration. Collaborate with stakeholders, produce actionable insights, validate analyses, participate in peer review, and iterate to improve products impacting millions of customers.

Work on machine learning research and prototypes: analyze algorithms on large datasets, design experiments, prepare and clean data for modeling, and implement scalable AI system prototypes under senior guidance.

Work on real-world software projects: design, develop, test, and improve software. Collaborate with stakeholders, learn new technologies, apply engineering principles, and enhance product reliability, performance, and observability in a team environment.

Own revenue growth for a portfolio of licensing and solution partners. Build C-suite relationships, create and execute Partner Business Plans, lead cross-functional PODs, drive renewals, co-sell, AI/Copilot and security motions, and run disciplined sales rhythms (MBR/QBR, pipeline, MCEM) to meet quarterly targets.

Senior Data & AI consultant responsible for designing, developing, and delivering cloud data and AI solutions on Microsoft platforms. Lead data engineering, platform modernization, ML readiness, MLOps, and Azure-based deployments while collaborating with customers and teams to drive adoption and technical excellence.

Partner with sellers and cross‑functional teams to orchestrate and execute complex Services deals across the quote‑to‑cash lifecycle. Ensure deal readiness, contract accuracy, compliance, and resolution of operational blockers while driving process improvements and adoption of AI‑enabled workflows to increase deal velocity and quality.

Lead architecture and development of reusable silicon firmware libraries, HAL, and low-level drivers for SoC platforms. Drive SoC bring-up, system-level debugging, performance tuning, and cross-team alignment. Mentor engineers and own firmware lifecycle from design through validation, manufacturing, and productization.

Design, implement, and deliver cloud-scale storage features for Azure Storage. Participate in requirements gathering, design documents, coding, estimation, monitoring and incident response as a DRI for simple issues. Improve availability, reliability, efficiency, observability, and performance of distributed, high-performance storage systems.

Design, build, and operate AI-powered cloud platform services for developer workflows across the application lifecycle. Own end-to-end architecture, implementation, deployment, and live-site operations for cloud-to-edge capabilities, integrations, and AI-enabled engineering systems. Emphasize reliability, security, and responsible AI practices while improving developer productivity and testing at scale.