Senior Researcher - Agentic AI - Microsoft Research AI Frontiers

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Research Sciences

Research Scientist focused on agentic AI, developing self-improving, multi-agent systems that learn through interaction. The role involves research on recursive self-improvement, adaptive coordination, continual learning, human-AI collaboration, and autonomous skill acquisition. It spans the research-to-deployment spectrum with a focus on building evaluation frameworks and synthetic data pipelines, and refining architectures for scalability. The work is grounded in foundation models and learning agent platforms, with potential for product impact and publication.

What you'd actually do

  1. As a Senior Researcher in the AI Frontiers lab, you will perform cutting-edge research in collaboration with other researchers, engineers, and product groups.
  2. As a member of a world-class research organization, you will be a part of research breakthroughs in the field and will be given an opportunity to realize your ideas on products and services used worldwide.

Skills

Required

  • Doctorate in relevant field OR Master's Degree in relevant field AND 3+ years related research experience OR Bachelor's Degree in relevant field AND 4+ years related research experience OR equivalent experience.

Nice to have

  • Research record demonstrated by public artifacts like models, tools, code in AI space or publications at the following conferences: NeurIPS, ICML, ICLR, ACL, NAACL, COLM
  • Expertise in the technical scaling of models and a commitment to engineering excellence, including the development of generalized code and robust research infrastructure.
  • Experience publishing academic papers as a lead author or essential contributor in the field of Artificial Intelligence, deep learning, natural language processing and/or reinforcement learning.
  • Experience participating in a top conference in relevant research domain (i.e. organizing a workshop, hackathon, community engagement/relations).
  • Demonstrable ability to define an ambitious, original research agenda
  • Ability to collaborate, communicate effectively, and technically lead multi-disciplinary team.
  • Keen interest in real-world applications and impact.

What the JD emphasized

  • expand the pareto frontier of Artificial Intelligence (AI) capabilities, efficiency, and safety
  • building an end-to-end agentic model stack
  • robust evaluation frameworks
  • high-fidelity synthetic data pipelines
  • recursive improvement
  • adaptive coordination
  • autonomous skill acquisition

Other signals

  • agentic intelligence
  • self-improving AI systems
  • multi-agent collaboration
  • continual learning
  • autonomous skill acquisition