Applied Scientist
Microsoft
Applied Scientist
Beijing, China
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Overview
The M365 Copilot RAG team is building the next generation of intelligent assistant systems to empower enterprise users with advanced productivity capabilities. We are hiring multiple Applied Scientists to join our efforts in enterprise-grade search, agentic RAG and multi-agent orchestration. As Applied Scientist, you will directly contribute to the core capabilities of Copilot and impact how millions of users interact with their enterprise data.
Our team is composed of world-class scientists and engineers who are passionate about turning cutting-edge research into high-quality, scalable products and services. We welcome junior and talented candidates to our team!
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.
Come build community, explore your passions and do your best work at Microsoft. This opportunity will allow you to bring your aspirations, talent, potential - and excitement for the journey ahead.
Qualifications
Required Qualifications:
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND relevant experience (e.g., statistics, predictive analytics, research)
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
- OR equivalent experience.
Preferred Qualifications:
- Strong algorithmic and modeling skills, with solid problem-solving capabilities.
- 1+ years' experience in NLP, RL, search, or recommendation systems for industry hire.
- Familiarity with complex document understanding, RAG frameworks, and multi-agent orchestration is a strong plus.
- Excellent communication and collaboration skills, with the ability to thrive in cross-functional environments.
Responsibilities
- Develop sub-agents for search, find, and related tasks over complex enterprise private data with diverse types and heavy schema.
- Optimize core algorithms for RAG systems, including retrieval, ranking, and grounding extraction.
- Explore novel task decomposition and execution strategies within multi-agent collaboration frameworks.
- Analyze offline and online performance signals to identify optimization opportunities and improve user experience and system efficiency.
- Collaborate closely with product and platform teams to deliver robust, scalable solutions.