| Company: | AMAZON |
|---|---|
| Job Role: | Machine learning scientist, TTS Research. |
| Experience: | (1-2 years). |
| Vacancy: | 25+ |
| Qualification: | BE/B.Tech, ME/M.Tech, Ph.D. or related degree. |
| Salary: | 112,909 EUR/year. |
| Location: | Germany. |
| Join us on Telegram | Click Here |
| Apply Mode: | (Online) |
| Deadline: | Not Mentioned |
Amazon is committed to fostering a diverse and inclusive work environment. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or any other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us. Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records
Description:
Job summary
Do you want to work on some of the most innovative Text-to-Speech technology in the industry? Well, you’ve come to the right place. We are looking for a passionate, talented, and inventive Machine Learning Scientist with a strong background in Machine/Deep Learning/NLP/Speech and Software Development to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Text-to-Speech (TTS) in order to provide the best-possible experience for our customers. Your role is to leverage your strong background in Computer Science and Machine Learning to help build the next generation of our synthetic voices used by millions of customers every day.
Key Job Responsibilities:
- We are seeking a Machine Learning Scientist to join our team to develop novel algorithms and modeling techniques to advance the state of the art in speech synthesis. Utilizing Amazon's heterogeneous data sources and large-scale computing resources, you will build Machine Learning models for speech synthesis.
- The role requires a pragmatic technical leader comfortable with ambiguity, capable of explaining complex data and models through clear visual and written explanations.
- Ideally, the candidate will have experience with machine learning models and their application in AI systems. Natural language processing, deep learning, and speech generation at scale are of particular interest to us. Additionally, we seek candidates with a strong interest in applied sciences and engineering, creativity, curiosity, and great judgment.
A day in the life
No two days are the same as a Applied Scientist at TTS Research!
You will be working in a dynamic, fast-moving environment. You’ll be developing new Deep learning models to improve the quality of our speech models, running experiments and writing papers and patents or making prototype solutions production ready.
About the team
This role sits with TTS, and the goal of the team is to create natural, friendly and emotional voices for Alexa.
Basic Qualification:
- Graduate degree (PhD or equivalent Master's) in fields such as Machine Learning, Deep Learning, TTS, ASR, NLP.
- Familiarity with programming languages such as Python, C/C++.
Preferred Qualification:
- Ph.D. in text-to-speech, natural language processing, or machine learning
- Expertise in machine learning research projects from two years of industry experience
- Expertise in deep learning and speech synthesis
- End-to-end agile software development experience
- Communicate complex technical concepts and solutions to all levels of the organization
- Publications record of high quality
EEO
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
How to Apply Click on the Below link, it will redirect you to source Page and apply there.
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