Sony Research India is driving cutting-edge research and development in various locations around the globe, including laboratories in Japan, the United States, Europe, and Asia. They endeavor to create new technology, products, and services while sustaining Sony Group’s diverse businesses in electronics, entertainment, and financial fields. For their research center to blaze a trail in the latest technologies, they seek to foster the growth of a diverse pool of research and engineering talent and create a technology talent bank to drive research excellence worldwide. Sony Research India is offering outstanding career opportunities around frontline technologies such as AI and data analytics. Candidates are advised to apply soon before the link expires
Name of the
Organization: Sony Research India
Requisition
ID: 4034726150
Positions: Data
Science Intern
Location: Remote (Work
from Home)
Salary: As per
company Norms
Educational
Qualifications:
- Master’s or Bachelor’s degree with relevant experience.
Duration of
the paid internship:
- The paid internship will be for 6 months starting first or second week of October 2024.
- The working hours are from 9:00 IST to 18:00 IST (Monday to Friday).
Must-Have
Skills:
- Strong understanding in Supervised and Unsupervised Machine learning models using Python
- Experience with PyTorch and TensorFlow and training deep learning models
- Experience in exploratory data analysis on Large Datasets
- Exposure to using AWS S3, Athena, and EC2
Good to Have
Skills:
- MLOps and Model Deployment
- Dashboard development
Responsibilities:
- Collaborate with research scientists and team members on daily activities, focusing on custom model training, development and optimization
- Build models from data (involves exploratory data analysis, hypothesis testing, predictive modeling)
- Use ML models as well as PyTorch and TensorFlow for deep learning model implementation, if required
- Employ AWS services such as S3, Athena, and EC2 for efficient data storage, querying, and computation
- Build dashboards for the predictive models.
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