Software Engineer II

Microsoft is a company where passionate innovators come to collaborate, envision what can be and take their careers further. This is a world of more possibilities, more innovation, more openness, and sky is the limit thinking in a cloud-enabled world.

The Artificial Intelligence (AI) Platform organization at Microsoft builds the end-to-end Azure AI stack/Platform as a Service (PaaS) and is core to Azure's innovation and differentiation, as well as all of Microsoft's flagship products, from Office to Teams, to Xbox. We are the team building Azure OpenAI, Azure Machine Learning (ML), Cognitive Services, and the global Azure AI infrastructure for running the largest AI workloads on the planet.

Within AI Platform, the AI Frameworks team makes ML practitioners and engineers more efficient through optimized libraries, tools, and communities. You will be responsible for designing, implementing, and testing functions or components for our AI/DNN frameworks and tools, improving performance and efficiency of our systems, and collaborating with internal and external partners.

The role offers the opportunity to work on cutting-edge AI technology, contribute to large-scale distributed computation systems, and be part of Microsoft's mission to empower every person and organization on the planet to achieve more. You'll be working in a fast-paced startup environment while having the resources and impact of a global technology leader.

We value diversity of thought and perspective, seeking out different viewpoints to create better solutions. Our inclusive culture encourages collaboration, innovation, and personal growth. You'll have access to industry-leading healthcare, educational resources, savings and investments opportunities, and generous time-away policies.

This position requires strong technical skills in software development, system programming, and machine learning, combined with the ability to drive cross-team collaboration and demonstrate technical leadership while maintaining humility and openness to feedback.