OverviewWe're looking for a Senior Applied Scientist to help define how AI systems understand, assemble, and reason over the world's information. Our team works on the core challenges that sit between raw data and intelligent action: information retrieval, context assembly, grounding, knowledge representation, and agentic reasoning. We are building the next generation of systems that transform fragmented data into coherent context, enabling agents to find the right information, understand relationships across sources, and act with confidence. This role requires a unique combination of research depth and product impact.
You will own the scientific foundations that enable agents and search systems to find, understand, organize, and ground their behavior in enterprise content. Develop representations, retrieval and ranking methods, context-assembly algorithms, and evaluation systems that make enterprise AI accurate, efficient, secure, and trustworthy. You will contribute new ideas and algorithms while also driving them into production systems used by millions of customers. Your work will shape the foundational capabilities that determine whether AI systems can move beyond answering questions to deeply understanding information landscapes, synthesizing knowledge, and accomplishing real-world tasks.
Responsibilities- Advance the state of the art in retrieval and context engineering, exploring approaches such as model fine-tuning, reinforcement learning, learned retrieval and context-selection policies, synthetic data, distillation, adaptive RAG, agent memory, and other emerging techniques.
- Own the end-to-end quality strategy for enterprise grounding, establishing evaluation methods and driving improvements in relevance, reasoning, factuality, citation quality, task completion, robustness, efficiency, and trustworthiness.
- Develop learning systems that improve from feedback, including user interactions, agent outcomes, human judgments, and production signals, while accounting for sparse feedback and changing enterprise content.
- Translate research into scalable product capabilities, partnering with engineering and product teams to move promising ideas from experimentation into reliable, secure, and cost-effective production systems.
- Identify and shape new research opportunities, maintaining awareness of emerging methods, developing prototypes, influencing technical architecture, and contributing publications, patents, or external research collaborations where appropriate.
- Provide scientific leadership, setting a high bar for experimental rigor, guiding technical decisions, mentoring others, and communicating findings and strategic recommendations across the organization.
QualificationsRequired Qualifications:- Bachelor'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)
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
Preferred Qualifications:- Master'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)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
- 3+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
- Experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
- 3+ years experience conducting research as part of a research program (in academic or industry settings).
- 1+ year(s) experience developing and deploying live production systems, as part of a product team.
- 1+ year(s) experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.
- Expertise with emerging approaches such as fine-tuning, preference optimization, synthetic data generation, distillation, adaptive retrieval, or learned context-selection policies.
- Publications, patents, open-source contributions, or demonstrated thought leadership in relevant areas of machine learning or artificial intelligence.
- Familiarity with privacy, security, permissions, governance, and responsible AI considerations in enterprise environments.
Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $160,200 - $261,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
