Senior Applied Scientist - Metrics
Microsoft
Senior Applied Scientist - Metrics
Redmond, Washington, United States
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Overview
The CoreAI Speech Group brings together talents in the areas of signal processing, speech modeling, statistical modeling and deep learning to develop and deliver robust, natural and scalable speech technologies, across a rich set of scenarios and languages. Our interdisciplinary team of scientists and developers work on all aspects of end-to-end speech technologies, including model training and evaluation, data collection, infrastructure, and service deployment. We are looking for a Senior Applied Scientist who is passionate about advancing the next generation of speech experiences by developing innovative tools and metrics for comprehensive evaluation of Azure AI services.
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.
In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.
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.
- 3+ years of experience in one or more of the following areas: speech recognition, large language models, machine learning, deep learning, pattern recognition, statistics.
- 2+ years of programming experience in Python with PyTorch.
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:
- 1+ years of experience in developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.
- 1+ years of experience in AI benchmarking, such as LLM, speech, computer vision, machine translation, and so on.
- 2+ years of experience in publication on top speech and machine learning conferences, such as ICASSP, InterSpeech, ASRU, ICML, ICLR, NeuroIPS, etc.
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
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Responsibilities
Innovate and develop novel benchmarking metrics to advance state-of-the-art speech technologies for real world user scenarios. Specifically, you will:
- Develop metrics highly correlated to human experience for model quality.
- Develop experimentation systems to assess system performance.
- Collaborate with engineering team to scale offline and online measurement system.
- Utilize diverse feedback channels (e.g., A/B testing, flight experiments, and log analysis) to assess the performance and reliability of speech systems in dynamic environments.
- Stay updated with the latest trends in speech technologies, large language models (LLM), and evaluation techniques, and apply knowledge to ongoing projects.