Microsoft Dynamics 365 suite of products, Power Apps, Power Automate, Dataverse, AI Builder, Microsoft Industry Solution and more. The Business and Industry Solutions (BIS) team is looking for this role to drive innovation at the intersection of AI, experimentation, and enterprise systems.
Requirements
- 1+ year(s) of generative AI experience.
- Applied Sciences IC2 - The typical base pay range for this role across the U.S. is USD $84,200 - $165,200 per year.
- There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $109,000 - $180,400 per year.
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
- Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)
- Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
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.
- Deliver impactful solutions by executing high‑leverage data science and analytics initiatives within a product area or feature team, ensuring measurable improvements to user and business outcomes.
- Lead the design and implementation of advanced model fine‑tuning pipelines, including Reinforcement Learning from Human Feedback (RLHF), to align AI system behavior with user intent and improve performance in real‑world scenarios.
- Own complex, end‑to‑end projects that combine technical depth with cross‑functional collaboration, influencing feature direction and prioritization rather than broad organizational investment decisions.
- Develop and maintain robust measurement systems, experimentation frameworks, and causal inference methodologies tailored to dynamic AI systems and enterprise‑scale environments.
Other
- 3 days / week in-office
- Travel 0-25%
- Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
- Microsoft is an equal opportunity employer.
