Senior Applied Scientist - Custom Speech
Job Description
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. As a science team in the Speech Group, we industrialized deep learning speech technologies and contributed key innovations to the speech community. We work on all kinds of end-to-end speech technologies, targeting the most challenging problems by inventing new algorithms. To that end, we welcome a Senior Applied Scientist to drive state-of-the-art speech modeling technologies, which impact millions of users. 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.
Locations
- Redmond, Washington, United States
Salary
119,800 - 234,700 USD / yearly
Estimated Salary Rangehigh confidence
180,000 - 260,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- automatic speech recognitionintermediate (speech technologies)
- speech translationintermediate (speech technologies)
- deep learning model trainingintermediate (machine learning)
Required Qualifications
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field (degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, 4 years)
- Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field (degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, 3 years)
- Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field (degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, 1 years)
- related experience (e.g., statistics, predictive analytics, research) (experience, 2 years)
- experience in automatic speech recognition or speech translation (experience, 2 years)
- experience in deep learning model training (experience, 2 years)
Preferred Qualifications
- experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping (experience, 1 years)
- experience developing and deploying live production systems, as part of a product team (experience, 1 years)
- experience conducting research as part of a research program (in academic or industry settings) (experience, 3 years)
- experience presenting at conferences or other events in the outside research/industry community as an invited speaker (experience)
- experience creating publications (e.g., patents, libraries, peer-reviewed academic papers) (experience, 3 years)
- Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field (degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, 6 years)
- Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field (degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, 3 years)
- experience presenting at conferences such as Automatic Speech Recognition and Understanding (ASRU), International Conference on Acoustics Speech and Signal Processing (ICASSP), Interspeech or other events (experience, 2 years)
Responsibilities
- Advance model capability to adapt to different domains.
- Develop techniques to leverage customer data to improve model quality.
- Develop techniques to adjust model behaviors for different scenarios.
Benefits
- healthcare: Industry leading healthcare
- education: Educational resources
- discounts: Discounts on products and services
- savings: Savings and investments
- leave: Maternity and paternity leave
- time_off: Generous time away
- giving: Giving programs
- networking: Opportunities to network and connect
Travel Requirements
0-25 %
