Expoint - all jobs in one place

Finding the best job has never been easier

Limitless High-tech career opportunities - Expoint

Microsoft Gen AI Principal Applied Scientist 
United States, California, Mountain View 
123450866

28.01.2025

As ayou will design and develop LLMs (Large Language Models) and underlying subsystems to tailor to various Search specific scenarios.

Required Qualifications:

  • Bachelor's Degree in Computer Science or Computer Engineering, or related field AND 8+ years related experience
    • OR Master's Degree in Computer Science, Electrical or Computer or related field AND 6+ years related experience
    • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience
    • OR equivalent experience.

Additional or Preferred Qualifications:

  • Doctorate or Master's Degree Computer Science, or Computer Engineering, or related field AND 10+ years related experience.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:Microsoft will accept applications for the role until January 30, 2025.


Responsibilities
  • Act as a leading expert in your field for a broad area of research, applying this knowledge to solve product-related problems. Champion innovative technologies related to industry trends, products, and other advances, and develop and share unique technical knowledge with teams.
  • Incorporate key business and product requirements to define a clear agenda and drive programs around key business challenges. Advise teams on methods, ensure quality and scientific rigor, and drive business impact.

  • Proactively provide mentorship and build your team’s capabilities. Establish best practices, serve as technical lead, build trusted relationships with internal and external stakeholders and drive efforts to attract, screen and interview top talent.

  • Drive discussions around ethics and privacy policies related to research and lead decision making efforts. Ensure that members across the discipline are aware of the potential for bias in the solutions being developed.