Senior Researcher - Multimodal AI - Microsoft Research AI Frontiers

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

Senior Researcher in Microsoft Research AI Frontiers lab focusing on expanding AI capabilities, efficiency, and safety through innovations in foundation models and learning agent platforms. The role involves research into Generative AI and Multimodal Model (MLM) technologies, including reasoning, architectures, training methods, action models, orchestration, multi-agent systems, and evaluation.

What you'd actually do

  1. Perform cutting-edge research in collaboration with other researchers, engineers, and product groups.
  2. Be a part of research breakthroughs in the field and will be given an opportunity to realize your ideas in products and services used worldwide.
  3. Embody our culture and values.

Skills

Required

  • Doctorate (or currently pursuing) in Computer Science or relevant field
  • Experience in Computer Vision and related fields.
  • Publications at NeurIPS, ICML, ICLR, ACL, NAACL, CVPR, COLT, ECCV, ICCV, EMNLP.

Nice to have

  • Doctorate in Computer Science or relevant field AND 2+ years related research experience
  • Experience publishing academic papers as a lead author or essential contributor in the field of Artificial Intelligence.
  • Experience participating in a top conference in relevant research domain.
  • Demonstrable ability to define an ambitious, original research agenda.
  • Ability to collaborate, communicate effectively, and work as part of a multi-disciplinary team.
  • Keen interest in real-world applications and impact.

What the JD emphasized

  • publications at the following conferences: NeurIPS, ICML, ICLR, ACL, NAACL, CVPR, COLT, ECCV, ICCV, EMNLP
  • Doctorate (or currently pursuing) in Computer Science or relevant field
  • Experience in Computer Vision and related fields.

Other signals

  • advancement of Generative AI and Multimodal Model (MLM) technologies
  • developing, improving, and exploring the capabilities of Multimodal AI models
  • reasoning method for multimodal models
  • new multimodal model architectures and training methods
  • action models for automating web and computer tasks
  • orchestration and multi-agent systems
  • evaluation and understanding of model and agent capabilities