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23 часа назад

Principal Applied Scientist (AI)

Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
China
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Principal Applied Scientist (AI): Developing core agentic systems for M365 Copilot with an accent on reasoning, memory management, and agent orchestration at enterprise scale. Focus on translating state-of-the-art research into production-ready features, defining scientific quality bars, and driving technical excellence within the AI team.

Location: Must be based in Beijing, China

Company

A global technology leader empowering every person and every organization on the planet to achieve more through innovative AI and productivity software.

What you will do

  • Design and ship advanced agentic AI techniques, including planning, reasoning, memory, and LLM post-training.
  • Translate cutting-edge research into scalable, reliable, and measurable production solutions.
  • Define quality bars and evaluation strategies for agent behavior, reasoning, and safety.
  • Diagnose system failure modes and drive systematic, data-driven improvements.
  • Provide technical leadership, mentor team members, and influence overall system architecture.

Requirements

  • Bachelor’s degree and 6+ years of experience, Master’s and 4+ years, or Doctorate and 3+ years in a relevant technical field.
  • Strong algorithmic and modeling skills with proven problem-solving capabilities.
  • Demonstrated expertise in multi-turn agent orchestration and LLM lifecycle.
  • Excellent communication skills for cross-functional collaboration.
  • Must be able to work on-site in Beijing, China.

Nice to have

  • Academic background or research focus in reinforcement learning (RL), agent systems, or search systems.
  • Experience with long-horizon tasks and context management.

Culture & Benefits

  • Opportunity to work on enterprise-grade AI products impacting millions of users.
  • Collaborative environment with access to massive-scale production data.
  • Strong culture of technical mentorship and scientific rigor.
  • Commitment to equal opportunity and workplace inclusivity.

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