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Generative AI Intern

Zupee

Updated on: 01 January 1970

Additional Details

Website

www.zupee.com

website

Work Location

Gurgaon, India

location

Job Type

FTE

job_type

Batch

Freshers/Experienced

batch

Stream Required

Previous experience with projects, internships, or research work related

stream

Salary

6 LPA (Expected)

salary

Job Description

About Zupee

 

Zupee is India’s fastest growing Technology backed Behavioral Science company. We are innovating Skill-

Based Gaming with a mission to become the most trusted and responsible entertainment company in the world. We have been constantly focusing on innovation of indigenous games to entertain the mass.

Our strategy is to invest in our people & user experience to drive profitable growth and become the market leader in our space. We have been experiencing phenomenal growth since inception and running profitable at EBT level since Q3, 2020. We have closed Series B funding at $102 million, at a valuation $600 million.

The company also announced a partnership with Reliance Jio Platforms, post which Zupee games will distribute its content across all customers using Jio phones. The partnership now gives Zupee the biggest reach of all gaming companies in India, transforming it from a fast-growing startup to a firm contender for the biggest gaming studio in India.

 

 

ABOUT THE JOB

 

Role & Responsibilities

1) Assist in the research, design, and development of generative AI models, to create innovative AI-driven solutions for image, text, or audio generation.

2) Experience with popular machine learning libraries and frameworks like TensorFlow, PyTorch, scikit-learn, or Keras.

3) Work with large datasets to preprocess data, conduct data augmentation, and train AI models, while continuously improving performance through model tuning and optimization techniques.

4) Build prototypes and proof-of-concept applications to demonstrate the capabilities of generative AI technologies, experimenting with new algorithms and approaches to push the boundaries of what's possible.

5) Document research findings, code, and experimental results clearly, and present insights and best practices

6) Previous experience with projects, internships, or research work related to machine learning, data science, or artificial intelligence.

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