Senior Applied Scientist

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This role is available in Mountain View, CA, Redmond, WA or New York, NY.

In this role, the Senior Applied Scientist will design and implement state-of-the-art machine learning models and algorithms that power key systems within Microsoft Ads, Microsoft Audience Network, Copilot, and beyond. Your work will directly impact millions of users and advertisers by delivering scalable solutions that enhance ad relevance and optimize user experiences.

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:

Preferred Qualifications:

• Proven experience in programming and data analysis skills.
• Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, or transformers.
  

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 and processes offers for these roles on an ongoing basis.

#MicrosoftAI #MAI, #MSAN, #Copilot

• Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.
• Design scalable algorithms for online and offline systems, delivering innovative solutions for content selection, user engagement modeling, and ad generation.
• Drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions.
• Build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications.
• Stay at the forefront of AI research, incorporating the latest advancements to drive innovation and impact across Microsoft platforms.