Principal Applied Scientist - Deep Learning for Audio and Video

24 Apr 2024
Job Information

Organisation/Company

Microsoft

Research Field

Computer science

Researcher Profile

Recognised Researcher (R2)

Country

Estonia

Application Deadline

23 May 2024 - 00:00 (UTC)

Type of Contract

To be defined

Job Status

Full-time

Hours Per Week

To be defined

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

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Responsibilities (Text Only)

- Apply machine learning to improve existing and develop new algorithms to improve Skype/Teams real-time collaboration quality and reliability
- Understand and be able to leverage core concepts of video and/or audio processing
- Design, develop, and own components, tools, platforms, and systems for real-time media communication and collaboration.
- Drive independent investigations resulting in shipping product code, patents, and publications

Qualifications (Text Only)

Required Qualifications:
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 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 related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.

- Experience in creating high performance speech enhancement models, both through shipping products and publications.
- Experience in machine learning, and using ML tools like Pytorch and TensorFlow.
- Solid system development skills, with a long-range system view that leverages development ranging from rapid research prototypes to carefully architected complex systems.
Preferred Qualifications:
- Master's Degree in Statistics, Econometrics, Computer Science, Electrical
- OR Computer Engineering,
- OR related field AND related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical
- OR Computer Engineering,
- OR related field AND related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.

- Experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
- Experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
- Experience conducting research as part of a research program (in academic or industry settings).
- Experience developing and deploying live production systems, as part of a product team.
- Experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

#M365

Requirements
Additional Information
Work Location(s)

Number of offers available

1

Company/Institute

Microsoft

Country

Estonia

Geofield

Where to apply

Website

https://illbeback.ai/job/principal-applied-scientist-deep-learning-for-audio-an…

STATUS: EXPIRED