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August 14, 2025

Senior Applied Scientist

Senior • On-site • Remote

$119,800 - $234,700/yr

Redmond, WA

Overview

Copilot Tuning is a new AI product that adapts based on tenant data, enabling customer-specific agents and solutions. We are a small, nimble team that is advancing the state of the art of models in M365 Copilot. Come join our team and help transform the LLM (large language model) experience in the enterprise.


We are seeking a Senior Applied Scientist with stellar research and system building skills and the desire to pursue the cutting edge in model development that pushes technological boundaries. We are looking for candidates with interest and experience in language model training, reinforcement learning, and supervised fine-tuning.

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.

Qualifications

Required 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.
  • 2+ years of experience training/fine tuning AI/ML models, preferably LLMs.
  • 2+ years of experience building Generative AI pipelines, e.g. with RAG (Retrieval augmented generation).
  • 2+ years of experience with Python and/or PyTorch.

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:

  • 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.
  • Deep knowledge of transformer models and architectures.
  • Experience with reinforcement learning algorithms and applications.
  • Experience working with customers deploying AI solutions.
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 $158,400 - $258,000 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    
  
Microsoft will accept applications for the role until August 26, 2025. 
 

 

#M365 #Copilot

Responsibilities

  • Train and deploy Language Models adapted to specific industry needs.
  • Create and adapt novel training and fine-tuning algorithms for tasks such as reasoning and search.
  • Identifies, researches, and implements machine learning solutions given product requirements.
  • Brings a research project to successful completion yielding new algorithms, prototypes, theories, tools, methods, analyses, insights, or collections of data which solve one or more open research problems.
  • Document and share best practices across the organization.
  • Supports mentorship by assisting with onboarding of research interns or other early in career team members.