Internship Catalogue

AI Developer Internship: Generative AI Applications
turqoicitconsulting llp

Title

AI Developer Internship: Generative AI Applications

Description

As an AI Developer Intern, you’ll work on exciting projects that push the boundaries of Generative AI, contributing to real-world applications such as text generation, image synthesis, conversational AI, and more. You’ll gain hands-on experience with state-of-the-art AI technologies while collaborating with a dynamic and passionate team.

What You’ll Be Doing

🤖 Designing, developing, and deploying Generative AI models for innovative applications.
📈 Training and fine-tuning machine learning models using deep learning frameworks such as TensorFlow and PyTorch.
🧠 Working with large datasets and pre-trained models like OpenAI GPT, DALL·E, Stable Diffusion, and others.
💡 Collaborating with the team to ideate, prototype, and implement cutting-edge AI solutions.
🔍 Optimizing models for performance, scalability, and cost-efficiency in real-world applications.

What You’ll Learn

  • Generative AI Mastery: Gain expertise in building AI applications for text, image, and audio generation.
  • AI Model Development: Understand the lifecycle of creating and deploying machine learning models.
  • Advanced Tools: Hands-on experience with AI libraries, cloud platforms, and version control tools like Hugging Face, TensorFlow, PyTorch, Dialogflow and Google Cloud AI.
  • Data Handling: Learn preprocessing, cleaning, and analyzing large datasets for AI training.
  • Integration: Discover how to integrate AI solutions into end-user applications.



No. of Openings : 10

Nature of Post : Full Time

Date of posting : 20th Nov 2024

Date of commencement : 20th Nov 2024

Additional Perks

Access to AI Tools

Qualification

Bachelors Degree or Diploma

CTC Range (Per Anum)

Not Paid

About the company

turqoicitconsulting llp

Internship Learning Outcomes

Generative AI Mastery: Gain expertise in building AI applications for text, image, and audio generation. AI Model Development: Understand the lifecycle of creating and deploying machine learning models. Advanced Tools: Hands-on experience with AI libraries, cloud platforms, and version control tools like Hugging Face, TensorFlow, PyTorch, Dialogflow and Google Cloud AI. Data Handling: Learn preprocessing, cleaning, and analyzing large datasets for AI training. Integration: Discover how to integrate AI solutions into end-user applications.
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