Principal Applied Science Manager, Copilot AI

We are looking for a Principal Applied Science Manger for the Business Copilot AI Team. Microsoft’s Business Applications Group is reimagining Dynamics 365 and the Power Platform applications using Generative AI, Large Language Models (LLMs), and copilots. The Microsoft Power Platform (Power Automate, Power Apps, Microsoft Copilot Studio, Power BI) is a rocket ship fueled by organizations across the globe investing in low-code/no-code development to accelerate their digital transformation ambitions. We are part of the AI team within Business Applications Group responsible for bringing AI to Enterprise solutions at scale. As part of this role, you will focus on building AI features using LLMs for Copilots powering the next generation of Automation solutions for Microsoft's Power Automate.

Power Automate is transforming Process Automation by seamlessly integrating Digital and Robotic Process Automation, by leveraging Artificial Intelligence and Natural Language Processing for smart automation and by enabling every human on the planet to use a low-code, no-code approach to automate end-to-end scenarios seamlessly across APIs (Application programming interface) and UI (User interface).

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

Responsibilities

AI is now undergoing a transformational change with the advent of LLMs and capable of making the next generation scenarios in Automation a reality. We are seeking a Principal Applied Science Manager with expertise in working with Large Language Models (LLMs) and other State of the art models to design scalable high fidelity systems. As a Principal Applied Science Manager, you will build and measure quality for systems that allow LLMs to reason over large amounts of data as well as leveraging lighter weight models for specific scenarios. We are looking for an individual who has experience working with product teams and partnering with them to deliver joint solutions. This can range from collaborating to build fine-tuned models to devising ways to construct LLM chains for specific product needs.

All models released in Microsoft products need to comply with Responsible AI (RAI) standards adhering to ethical principles, respect human values, and promote social good.  You will be ensuring everything you ship helps copilots be responsible AI systems. These include detecting harmful behavior, ungrounded/hallucinated answers, or jailbreak attempts. 

Embody our Culture and Values

Qualifications

Basic Qualifications:

• 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)
  • OR 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)
  • 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.
• 1+ year(s) people management experience.
• 5+ years experience writing production code as well as deploying and maintaining shipped models over time.
• 2+ years experience with leading Machine Learning projects and managing team of data scientists.
• 2+ years experience working on deep learning architectures specifically with Natural language-based models, vector databases and graph databases. 

Preferred Qualifications:

• Practical experience developing applications using prompt engineering, fine tuning, Open AI or Azure Open AI APIs.
• Experience collaborating effectively across partner teams.
• Experience in Deep learning architectures and implementation using Pytorch or TensorFlow.
• 2+ years experience architecting ML systems and designing data generation pipelines, experimentation plans, setup metrics etc.

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