The Business and Industry Solutions (BIS) team at Microsoft is looking for a Principal Applied Scientist to drive innovation in AI, experimentation, and enterprise systems, aiming to improve accuracy, latency, and cost-efficiency of autonomous agents.
Requirements
- Prior expertise in natural language processing (NLP), with a strong foundation in large language model (LLM) development, evaluation, and fine-tuning.
- Hands-on experience in applying advanced fine-tuning techniques—including instruction tuning, reinforcement learning from human feedback (RLHF), and tool-augmented generation—to build agents capable of multi-step reasoning and decision-making.
- Familiarity with prompt engineering, context-aware orchestration, and integrating LLMs with external tools and APIs is essential.
- Comfortable working in a fast-paced, experimentation-driven environment, leveraging both offline and online evaluation methods to iterate rapidly and optimize agent behavior.
- Deep understanding of the challenges and opportunities in building AI-native enterprise applications.
- 5+ years experience developing and deploying AI/ML products or systems at multiple points in the product cycle from ideation to shipping.
Responsibilities
- Design and evaluate autonomous agents that deliver measurable improvements in accuracy, latency, and cost-efficiency.
- Lead rapid experimentation cycles, develop robust evaluation frameworks, and apply advanced techniques like reinforcement learning to enable multi-step reasoning and decision-making.
- 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.
- Lead the development and deployment of advanced model fine-tuning pipelines, leveraging Reinforcement Learning from Human Feedback (RLHF) to align AI system behavior with human intent and improve performance in complex, real-world enterprise scenarios.
- Design and implement robust measurement systems, experimentation frameworks, and causal inference methodologies tailored to dynamic AI systems and enterprise-scale environments.
- Harness AI to accelerate workflows and amplify team productivity through intelligent automation and innovation.
- Apply advanced techniques like reinforcement learning to enable multi-step reasoning and decision-making.
Other
- Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
- This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
- Steer strategic direction and investment decisions by owning complex, end-to-end projects that blend technical depth with organizational influence.
- Build alignment and trust across leadership and cross-functional teams through clear, persuasive communication and collaborative engagement.
- Mentor and elevate the data science community by championing best practices, nurturing talent, and cultivating a collaborative, high-performance culture.
