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Mountain View, United States

Member of Technical Staff, Applied Scientist Member of Technical Staff, Applied Scientist

Location
Mountain View, United States
Job Number
1970324837133660-en-1
City
Mountain View
Category
Copilot
Country
United States
Discipline
Applied Science
Overview:
We’re seeking a Member of Technical Staff – Applied Scientist to help design and build advanced Copilot features such as Deep Research and Web artifact generation. This role demands deep expertise in large language models (LLMs) and a strong architectural mindset to shape complex, user-facing systems. You’ll contribute to the evolution of Copilot by developing scalable methods for evaluating feature performance, designing data collection pipelines for prompt engineering and fine-tuning, and training content classifiers that support intelligent, context-aware interactions.
The ideal candidate brings hands-on experience in building applications powered by LLMs, along with a solid foundation in data science and machine learning. You’re a proactive collaborator who communicates clearly, thrives in fast-paced environments, and takes ownership of delivering world-class consumer experiences. If you enjoy pushing the boundaries of AI-driven products and working across disciplines to create intuitive, high-impact solutions, we’d love to hear from you.
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
By applying to this U.S. Mountain View, CA position, you are required to be local to the San Francisco area and in office 3 days a week.
Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction.
Responsibilities:
  • Architect and implement advanced Copilot features such as Deep Research and Web artifact generation
  • Lead evaluation efforts of models deployed within Copilot, ensuring performance aligns with product goals
  • Design scalable systems that leverage large language models (LLMs) to deliver intelligent, user-facing experiences
  • Develop evaluation frameworks and metrics to assess feature performance and user impact
  • Conduct thorough reviews of data analysis and techniques to identify gaps and areas for re-examination
  • Build data collection pipelines to support prompt engineering and fine-tuning of LLMs
  • Track advances in industry and academia, identify relevant state-of-the-art research, and adapt algorithms to drive innovation
  • Train and optimize content classifiers to enable context-aware interactions within Copilot
  • Independently write efficient, readable, and extensible code and model pipelines
  • Contribute to defining the model quality roadmap for Copilot, balancing technical rigor with business and product priorities
  • Collaborate cross-functionally with product, engineering, and research teams to ship high-quality consumer features
  • Commit to a customer-oriented focus by validating customer perspectives, understanding broader context, and serving as a trusted advisor
  • Communicate technical concepts clearly and contribute to team-wide knowledge sharing
  • Take initiative in a fast-paced environment, driving innovation and continuous improvement in AI-powered products
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.
  • Experience prompting, evaluating, and working with large language models.
  • Experience writing production-quality Python code.
Preferred 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.
  • Demonstrated interest in Responsible AI.
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.
Applied Sciences IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 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 $188,000 – $304,200 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 and processes offers for these roles on an ongoing basis.
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