Principal Applied AI Scientist

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As a Principal Applied AI Scientist for The Customer Service Applications Team, you will play a pivotal role in advancing Microsoft's mission to empower every individual and organization on the planet to achieve more. You will contribute to the development and integration of cutting-edge AI technologies into Microsoft products and services, ensuring they are inclusive, ethical, and impactful.

You will collaborate across product, research and engineering teams to bring innovative solutions to life, applying your expertise in machine learning, data science, and AI to solve complex problems. Your work will directly influence product direction and customer experiences.

AI Mission and Impact
We are in an era of unprecedented innovation and openness. As Microsoft continues to lead in AI, we are seeking individuals to help tackle some of the most exciting and meaningful challenges in the field. Our vision is to build a truly open architecture platform that enables users to summon tailored AI agents to drive real-world outcomes.

We are looking for a Principal Applied AI Scientist to join our team.
This role will combine AI knowledge with applied science expertise, and demonstrate a growth mindset and customer empathy. Join us in shaping the future of AI agents.

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 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.
• 6+ years of Professional Software Engineering / AI experience.

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:

• Familiarity with modern LLMOps frameworks (e.g., LangChain, PromptFlow).
• 3+ years of experience publishing in peer-reviewed venues or filing patents.
• Experience presenting at conferences or industry events.
• 3+ years of experience conducting research in academic or industry settings.
• 1+ year of experience developing and deploying live production systems.
• 1+ years of experience working with Generative AI models and ML stacks.
• Experience across the product lifecycle from ideation to shipping.

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 for the role until November 6, 2025.

#BICJobs #CESJOBS

• Build collaborative relationships with product and business teams to deliver impactful AI solutions.
• Research, implement, and fine-tune state-of-the-art AI models using advanced techniques like foundation models, prompt engineering, and multi-agent architectures.
• Rapidly prototype AI solutions, deploy them to production, debug code, and support MLOps/AIOps workflows.
• Translate research into production-ready solutions, measure impact through A/B testing and telemetry, and contribute to papers, patents, and conferences.
• Use data to identify gaps in AI quality, uncover insights, and implement proof-of-concept projects.
• Maintain clear documentation of experiments and share findings internally to promote innovation and knowledge sharing.