GenAI Intern

Job Description:

As a GenAI Intern, you will work on developing and fine-tuning advanced AI models, exploring Generative AI (GenAI), Large Language Models (LLMs), Deep Learning, and Computer Vision applications. You will gain hands-on experience with state-of-the-art AI tools and frameworks while working alongside experienced AI professionals.

Key Responsibilities:

• Work on Generative AI models, fine-tuning pre-trained LLMs (e.g., GPT, BERT, LLaMA).
• Implement and optimize Deep Learning and Computer Vision models.
• Utilize TensorFlow, PyTorch, Hugging Face Transformers, LangChain, and related frameworks.
• Develop and train models for Object Detection and Image Recognition using YOLO, OpenCV.
• Conduct research and experiment with prompt engineering and model optimization techniques.
• Collaborate with the development team to integrate AI models into real-world applications.

Who Can Apply?

We are looking for candidates who:
✅ Are available for a 6-month internship.
✅ Have completed projects in GenAI, Deep Learning, and Computer Vision.
✅ Have a strong understanding of LLMs, Transformers, NLP, and Image Processing.
✅ Are proficient in Python, TensorFlow, PyTorch, and OpenCV.
✅ Are passionate about AI and eager to learn and innovate.

Perks & Benefits:

Certificate & Letter of Recommendation upon completion.
Flexible Work Hours – Work at your convenience.
Exposure to Cutting-Edge AI Technologies.
Collaborative Learning Environment with industry experts.

How to Apply?

If you are interested in this exciting opportunity, send your resume to [email protected] with the subject line "Application for GenAI Internship – Ai India".

Join us in shaping the future of AI!

Job Type: Internship
Contract length: 6 months

Pay: ₹5,000.00 - ₹18,000.00 per month

Application Question(s):

• Which of the following AI frameworks have you used?

TensorFlow
PyTorchHugging Face TransformersLangChainOpenCVYOLO

• Do you have experience working with Generative AI models?
• Have you worked on projects involving Deep Learning and Computer Vision?

Work Location: In person