Generative AI Intern - Internship

About the internship:Selected intern's day-to-day responsibilities include:

1. Build, test, and optimize Generative AI applications using LLMs, prompt engineering, Retrieval-Augmented Generation (RAG), and AI agents.

2. Develop practical prototypes, effective prompting strategies, and robust RAG pipelines.

3. Integrate LLMs with external APIs and tools while adhering to Responsible AI practices.

4. Prepare technical documentation, deliver demonstrations, and present project outcomes.

5. Collaborate with AI engineers and researchers to explore and implement emerging AI use cases.

6. Mentor students through technical training sessions and hands-on learning activities.

7. Travel to multiple locations as required.

8. Develop technical content and learning materials for projects and ongoing programs.Who can apply:Only those candidates can apply who:are available for full time (in-office) internshipcan start the internship between 13th Oct'26 and 17th Nov'26are available for duration of 6 monthshave relevant skills and interests* Women wanting to start/restart their career can also apply.Stipend:INR₹ 10,000 - 15,000 /monthDeadline:[hidden]:59:59Other perks:Certificate, Letter of recommendation, Flexible work hours, 5 days a weekSkills required:Python, Machine Learning, Neural Networks, Deep Learning, Generative AI Development and Python LibrariesAbout Company:SmartBridge is specialized in emerging technologies like IoT, machine learning, deep learning, augmented reality, virtual reality, embedded systems for IoT. We provide training & product consultation in the above technology domains. SmartBridge is one of the ed-tech partners of IBM India Private Limited.

Responsibilities

Selected intern's day-to-day responsibilities include:

1. Build, test, and optimize Generative AI applications using LLMs, prompt engineering, Retrieval-Augmented Generation (RAG), and AI agents.

2. Develop practical prototypes, effective prompting strategies, and robust RAG pipelines.

3. Integrate LLMs with external APIs and tools while adhering to Responsible AI practices.

4. Prepare technical documentation, deliver demonstrations, and present project outcomes.

5. Collaborate with AI engineers and researchers to explore and implement emerging AI use cases.

6. Mentor students through technical training sessions and hands-on learning activities.

7. Travel to multiple locations as required.

8. Develop technical content and learning materials for projects and ongoing programs.