Sony Remote Internship 2025; Hiring Data Science Intern – Apply Now

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.

Name of the Organization: Sony Research India

Requisition ID: 4127149988

Positions: Data Science Intern

Location: Remote (WFH)

Salary: As per company Norms

Duration of the paid internship:

• The paid internship will be for 3 months starting first week of February 2025.
• The working hours are from 9:00 IST to 18:00 IST (Monday to Friday).

Educational Qualifications:

• Bachelor's or Masters degree

Must-Have Skills:

• Hands-on experience in Python programming.
• Expertise in Supervised and Unsupervised Machine learning models.
• Proficiency in PyTorch, standard machine learning modules and TensorFlow.
• Experience with AWS S3, Athena, and EC2.
• Familiarity with deep learning/machine learning frameworks including scikit-learn.
• Knowledge of custom training and development of deep learning models on large datasets.

Good to Have Skills:

• Expertise in PyTorch.
• Previous experience in developing deep learning models.
• MLOps and Model Deployment.

Responsibilities:

• Collaborate with research scientists and team members on daily activities, focusing on dashboard development, ML/DL models training, development, and optimization.
• Utilize PyTorch and TensorFlow for deep learning model implementation.
• Employ AWS services such as S3, Athena, and EC2 for efficient data storage, querying, and computation.
• Gain insights into data cleaning techniques, MLOps practices, and dashboard development for predictive models.

 

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