Principal Applied Scientist

The Business & Industry Copilots (BIC) 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 Principal Applied Scientist to join our team.

The BIC Agent Cloud organization at Microsoft is among the most thrilling to be a part of. BIC Agent Cloud products herald a new era of business applications that are data-initiated, AI-driven, built for collaboration, and simplify business problem-solving with low-code/no-code platforms. Our team is responsible for developing the platform for Dynamics 365 suite of business applications, and the Power Platform suite of low-code tools. We are at the vanguard of digital transformation, enabling organizations to revolutionize the creation of Copilots through state-of-the-art AI solutions and product offerings. This new productivity era leverages the power of data, AI, and productivity tools to deliver unmatched experiences across all channels.

This role will operate at the frontier of AI science and product innovation, driving the design and deployment of next-generation AI systems at scale. You will need to design and build systems that allow LLMs to reason over large amounts of data as well as leveraging lighter weight models in place for specific scenarios for specific scenarios.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. 

Required Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ 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 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 5+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.

• 3+ years' experience developing and deploying large language models (LLMs), including agentic systems, supervised fine-tuning, and Reinforcement Learning (RLHF)
• 3+ years' experience designing, implementing, and optimizing Retrieval-Augmented Generation (RAG) pipelines and advanced context engineering.

Other Requirements:

• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
  • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred Qualifications: 

• 5+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
• Hands-on experience with modern LLM evaluation techniques, including LLM-as-a-Judge, agentic evaluations, and RAG assessments.
• A track record of delivering successful, large-scale applied ML projects in an industry setting.
• Deep understanding of fundamental ML algorithms (supervised, unsupervised) and modern neural network architectures.
• Experience with MLOps practices, including model versioning, automated testing, monitoring, and CI/CD for machine learning.
• A record of publication in top-tier scientific venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, KDD).

Applied Sciences IC6 - The typical base pay range for this role across the U.S. is USD $163,000 - $296,400 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 $220,800 - $331,200 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

Microsoft will accept applications for the role until August 6, 2025. 

#BICJOBS #BACJOBS

Responsibilities:

• Lead the design and development of advanced AI models and agentic systems for real-world applications.
• Own and drive end-to-end model training, including data pipeline design, distributed training optimization, and performance evaluation.
• Stay up to date with the latest advancements in LLM, NLP, deep learning, search and AI research.
• Research and develop an understanding of the state-of-the-art tools, technologies, and methods being used in the research community and product groups.  Drive innovation by staying current with the latest research, technologies, and best practices in AI/ML, and Translate research breakthroughs into production-ready algorithms, contributing to core capabilities such as search, planning, and long-term memory.
• Collaborate closely with engineering, product, and research teams to productionize models, build scalable, robust pipelines and provide support for in production AI Models/Agents
•   Lead end-to-end lifecycle of machine learning models, from prototyping and implementation to evaluation, deployment, and monitoring.
• Conduct applied science experiments, create and validate metrics, develop ML pipeline and modeling algorithm in the area of Large Language Models, Natural Language Processing, Information Retrieval, and Machine Learning.  
• Conduct experiments to evaluate model performance (including Large Language Models), troubleshoot issues, and iterate improvements