Sony Fresher Recruitment 2025 | Data Science Intern | Remote

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. We endeavor to create new technology, products, and services while sustaining Sony Group’s diverse businesses in electronics, entertainment, and financial fields. For our research center to blaze a trail in the latest technologies, we 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.

Work Location:

• Remote work within India.

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).

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Education:

• Bachelor’s or Masters degree

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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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.

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