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Come join Microsoft Office AI team to work on state-of-the-art services, AI solutions, platforms, distributed systems, and modern technology to deliver the next generation of intelligent productivity experiences used by hundreds of millions of users daily! We are looking for ML Engineer who can help us further grow our products, business, and culture! As ML Engineer in the Office AI team, you will help lead the evolution of Office productivity through AI-driven experiences (such as Microsoft Copilot) across key applications. The team builds the core platforms and experiences that bring large language models (LLMs) and real-time intelligence into Office applications, combining the power of LLMs with enterprise data and native integration to streamline content creation, navigation and comprehension. We are looking for a creative ML Engineer who will collaborate with software engineers, researchers, and product managers to express product needs as well-defined machine learning problems, push the state of the art in LLMs and bring prototypes all the way to planet scale production. You’ll build the engineering that makes AI work in production: you will build APIs, platforms and services around AI features; design data pipelines and feedback loops; deploy and finetune state of the art deep learning models; orchestrate prompts and tools; and monitor AI specific signals - such as drift, hallucinations, safety and cost - alongside traditional service reliability metrics. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Job Responsibility:
Ship features with PM & Engineering. Co-own scenario goals
translate product requirements into scientific plans and productionized solutions that meet quality/latency/cost targets.
Generative AI and advanced technologies. Apply knowledge of generative AI, large language models, and modern frameworks to develop intelligent features and automation within the service.
Azure platform integration. Deploy, integrate, and manage AI powered solutions within the Azure ecosystem, ensuring security, scalability, and compliance with best practices.
Continuous learning and mentoring. Stay current with advances in generative AI and software engineering. Invest time in learning new tools and frameworks, propose improvements to build processes, and share knowledge with colleagues.
Requirements:
BS in Computer Science, Electrical/Computer Engineering, Statistics, Mathematics, or related field (or equivalent experience).
AI and machine learning skills. Hands-on experience with generative AI or machine learning frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and a solid understanding of LLM concepts, embeddings, and prompt engineering.
Distributed systems and cloud. Familiarity with Azure services, microservices architectures, and distributed storage systems (experience with Cosmos DB or similar is a plus). Ability to design and run fault tolerant infrastructure on a large scale and to implement secure, compliant solutions.
Security and compliance. Ability to meet Microsoft’s and customers’ security and background check requirements.
Nice to have:
Master’s degree in computer science or related field.
Experience designing and running infrastructure systems that operate globally on a large scale.
Experience deploying AI models into production environments and building systems that monitor and retrain models automatically.
Passion for mentoring others and contributing to an inclusive team culture.