Senior Applied Scientist - CoreAI Voice Agent

Microsoft•Redmond, WA
•$119,800 - $261,000

About The Position

The CoreAI Voice Agent team develops robust, natural, and scalable speech technologies across scenarios and languages, combining signal processing, speech modeling, statistical modeling, and deep learning. The Senior Applied Scientist will work at the intersection of deep learning, signal processing, and speech/audio modeling to advance natural, expressive, and multilingual speech generation. The work supports conversational AI and accessibility products.

Requirements

  • Bachelor's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field and 4+ years of related experience, or a master's degree in one of these fields and 3+ years of related experience, or a doctorate in one of these fields and 1+ year of related experience, or equivalent experience.
  • Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.

Nice To Haves

  • 3+ years of experience developing and deploying products or systems at multiple points in the product cycle, from ideation to shipping.
  • Master's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field and 6+ years of related experience, or a doctorate in one of these fields and 3+ years of related experience, or equivalent experience.

Responsibilities

  • Design and develop novel speech algorithms, focusing on real-world applications in speech generation.
  • Address scalability challenges by aligning solutions with evolving stakeholder requirements.
  • Use large-scale computing frameworks, data analysis platforms, and modeling environments to improve model performance and efficiency.
  • Deploy models into production environments and iterate based on empirical results and user impact.
  • Evaluate multiple models in live scenarios through rigorous experimentation to compare performance.
  • Monitor deployed algorithms to ensure they meet expected behavior, accuracy thresholds, and performance guardrails.
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