Applied Scientist 2 (AI)

TL;DR

Principal Applied Scientist (AI): Leading the science roadmap for a next-generation Grounding Service that powers AI applications with factual, cited, and trustworthy responses, with an accent on retrieval, re-ranking, attribution, and reasoning methods. Focus on designing and evolving state-of-the-art RAG orchestration, building citation systems to reduce hallucinations, and productionizing models with scalable inference.

Location: This is an onsite role in Beijing, China. Employees are expected to work from the office at least four days per week if they live within a 25-mile commute of a designated Microsoft office.

Company

hirify.global is building the next-generation Grounding Service that powers AI applications like chat assistants, copilots, and autonomous agents.

What you will do

• Lead the science roadmap for grounding, including retrieval, re-ranking, attribution, and reasoning.
• Design and evolve state-of-the-art retrieval and RAG orchestration across various data types.
• 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 platform engineering to productionize models with scalable inference.
• Mentor applied scientists and collaborate cross-functionally to align on milestones and safety protocols.

Requirements

• Bachelor’s Degree with 2+ years, Master’s with 1+ year, or Doctorate in Statistics, Computer Science, Electrical/Computer Engineering, or related field.
• 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 a strong foundation in machine learning.
• Demonstrated ability to lead through ambiguity, make principled trade-offs, and deliver measurable impact.

Nice to have

• Bachelor’s Degree with 5+ years, Master’s with 3+ years, or Doctorate with 1+ year experience in related fields.
• 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, SFT, and reinforcement learning.
• Proven track record in optimizing LLM inference or active contributions to open-source frameworks.

Culture & Benefits

• Foster curiosity, pragmatic rigor, and inclusive collaboration.
• Empower every person and organization with a growth mindset, innovation, and shared goals.
• Cultivate a culture of inclusion based on respect, integrity, and accountability.
• Equal opportunity employer with consideration for all qualified applicants.