Applied Scientist 2 (AI)

TL;DR

Applied Scientist 2 (AI): Developing a next-generation grounding service to provide factual and trustworthy responses for AI applications like chat assistants and copilots, focusing on retrieval, reasoning, and real-time data integration. Focus on inventing retrieval and attribution methods, defining factuality metrics, and shipping production models that scale to billions of queries.

Location: Suzhou, China

Company

Microsoft’s mission is to empower every person and every organization on the planet to achieve more.

What you will do

• Own the science roadmap for grounding, including retrieval, re-ranking, attribution, and reasoning.
• Build citation and provenance systems to reduce hallucinations and increase user trust.
• Advance tool-augmented grounding through schema-aware retrieval and real-time connectors.
• Partner with product and business leaders to influence strategic decisions and drive business impact.
• Mentor applied scientists and data scientists, establishing best practices in experimentation and error analysis.
• Contribute to ethics and privacy policies, identifying bias in product development, and propose mitigation strategies.

Requirements

• Bachelor’s Degree in Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience OR Master’s Degree AND 1+ year of experience OR Doctorate.
• Minimum of 2 years of hands-on experience designing and building search, retrieval, or ranking systems.
• Proven track record of shipping LLM-powered or Retrieval-Augmented Generation (RAG) systems into production environments.
• Solid coding skills and solid foundation in machine learning.
• Demonstrated ability to lead through ambiguity and deliver measurable impact in cross-functional settings.

Nice to have

• Bachelor’s Degree AND 5+ years related experience OR Master’s Degree AND 3+ years related experience OR Doctorate AND 1+ year(s) related experience.
• Minimum of 4 years of hands-on experience designing and building search, retrieval, or ranking systems.
• Demonstrated expertise in information retrieval with publications in top-tier conferences or journals.
• Hands-on experience in large language model (LLM) development, including pretraining, supervised fine-tuning (SFT), and reinforcement learning (RL).
• Proven track record in optimizing LLM inference, or active contributions to open-source frameworks.

Culture & Benefits

• Growth mindset and inclusive collaboration are valued.
• Innovate to empower others and collaborate to realize shared goals.
• Build on values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive.