Artificial Intelligence (AI) Internship

Selected intern's day-to-day responsibilities include: 1. Develop and deploy LLM-powered applications and services. 2. Build and integrate AI/ML models as REST API services for frontend and client applications.

3. Use frameworks like Flask, FastAPI, or Django to create scalable and efficient backend systems. 4. Work with well-known generative AI models (e.g., GPT, LLaMA, Qwen, etc.

) for text, code, or content generation. 5. Collaborate with frontend developers and product teams to design and deliver AI-driven features. 6. Monitor and optimize performance, scalability, and cost of AI services.

7. Write clean, testable, and production-ready code with proper documentation. Who can apply: Only those candidates can apply who: • are available for full time (in-office) internship • can start the internship between 18th Sep'26 and 23rd Oct'26 • are available for duration of 6 months • are from Mumbai only • have relevant skills and interests Stipend: INR₹ 8,000 - 12,000 /month Deadline: 2026-10-18 23:59:59 Other perks: Certificate Skills required: Python and Artificial intelligence Other Requirements: • • 1.

Strong proficiency in Python. • 2. Good understanding of LLMs (architecture, fine-tuning, prompting, embeddings). • 3. Experience with Flask, Django, or FastAPI for API development.

• 4. Knowledge of how to consume and expose AI models as APIs. • 5. Familiarity with generative AI models such as GPT, LLaMA, Qwen, etc. • 6. Understanding of databases and persistence for storing AI inputs/outputs.

• 7. Proficiency with Git and collaborative development workflows. About Company: At Tax-O-Smart, we develop highly innovative and creative products and services that provide total tax and accounting solutions to all kinds of business structures.

Additional information: • Position Overview We are looking for a talented AI/ML Engineer with a strong background in Large Language Models (LLMs) and backend development to help us integrate Generative AI into real-world applications.

The ideal candidate should have hands-on experience deploying AI models as APIs, building scalable services using Python frameworks, and working with popular generative AI models.