Microsoft-posted 2 months ago
Senior
Redmond, WA
5,001-10,000 employees

The Business & Industry Copilots group is a rapidly growing organization that is responsible for the Microsoft Dynamics 365 suite of products, Power Apps, Power Automate, Dataverse, AI Builder, Microsoft Industry Solution and more. Microsoft is considered one of the leaders in Software as a Service in the world of business applications and this organization is at the heart of how business applications are designed and delivered. We are looking for a Senior Applied Scientist to join our team! The Business and Industry Solutions (BIS) team is looking for a Senior Applied Scientist to drive innovation at the intersection of AI, experimentation, and enterprise systems. In this role, you will design and evaluate autonomous agents that deliver measurable improvements in accuracy, latency, and cost-efficiency. You’ll lead rapid experimentation cycles, develop robust evaluation frameworks, and apply advanced techniques like reinforcement learning to enable multi-step reasoning and decision-making. You will collaborate across engineering, product, and partner teams to ensure agents are performant, secure, reliable, and extensible—empowering customers and partners to build on our platform. This is your opportunity to influence the next generation of AI-native business applications and deliver real-world impact at scale.

  • Design and evaluate autonomous agents for measurable improvements in accuracy, latency, and cost-efficiency.
  • Lead rapid experimentation cycles and develop robust evaluation frameworks.
  • Apply advanced techniques like reinforcement learning for multi-step reasoning and decision-making.
  • Collaborate with engineering, product, and partner teams to ensure agent performance, security, reliability, and extensibility.
  • Prior expertise in natural language processing (NLP).
  • Strong foundation in large language model (LLM) development, evaluation, and fine-tuning.
  • Hands-on experience in advanced fine-tuning techniques including instruction tuning and reinforcement learning from human feedback (RLHF).
  • Familiarity with prompt/context engineering and context-aware orchestration.
  • Experience integrating LLMs with external tools and APIs.
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