Sony Recruitment Remote Work
Sony Recruitment off-campus 2023 has announced a new job opening for the position of Intern at Sony. This is a fantastic opportunity for students from various disciplines who are looking to start their careers in the field of Intern. All the necessary details about Sony Recruitment 2023, including job responsibilities, eligibility criteria, and the application process is given below
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About Sony :
Sony Research India Private Limited was established in July 2020 as a research company in India as part of Sony’s global R&D centres. Delivering Excitement, Passion, Joy, and Compassion to the World, all is possible with the diverse research opportunities we offer at Sony Research India. We venture into entertainment, healthcare, music and gaming. We also devise mobility solutions that help people get around securely and safely and support creators expand their creativity with innovative AI applications. Sony Research India is a place to apply a wide range of technologies to inspire emotion in new fields.
Sony Recruitment 2023:
Company Name – Sony
Post Name – Speech Generation Intern
Salary – up to ₹40K/Month*
Experience – 0-2 yrs
Job Location – Remote/Bangalore/Mumbai
Batch – 2023/22/21/20/19/18
Website – www.sony.com
Sony Recruitment Job Description:
Sony is hiring candidates for the post of Intern.
Sony Recruitment Job Responsibilities:
Together with the research scientists or other team members, work on the basic development activities on a daily basis, and participate in speech generation-related topics of the project, like the development of the TTS/Voice Cloning System.
Duration:
6 months
9:00 to 18:00 (Monday to Friday) fulltime.
Sony Recruitment Eligibility Criteria:
Ph.D. or Master from Computer Science background or Bachelor with hands-on experience in Generative models with applications audio/speech.
Sony Preferred skill:
Python
Deep Learning/Machine Learning frameworks: Pytorch, Tensorflow, scikit-learn
Knowledge of the state-of-the-art in TTS/Voice Cloning/ Voice Conversion
Knowledge of generative models.
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