Job Description
Job Title: AI Intern (LLMs & Voice AI)
Internship Duration:6 Months
Employment Type: Internship (Full-Time)
Work Mode: Onsite (Work from Office)
Location: Brookfield, Bangalore
Stipend: 15,000 per month
Conversion Opportunity: Performance-based Full-Time Role
Eligibility
Engineering students / recent graduates from 2025, 2026, or 2027 batches
Branches: Computer Science, IT, AI & Data Science, AI/ML, Data Science, or related fields
About The Role
We are seeking a hands-on AI Intern with strong interest and practical exposure to Large Language Models (LLMs) and Voice-based AI systems. This 6-month onsite internship is designed for candidates who have already worked on AI, LLM, or voice-based projects and want to deepen their experience in building real-world, production-oriented AI solutions.
Key Responsibilities
Design and build LLM-powered applications using OpenAI or equivalent platforms
Develop and test voice-enabled AI pipelines, including Speech-to-Text (STT) and Text-to-Speech (TTS)
Work on voice-based conversational systems and LLM-driven assistants
Assist in prompt design, response tuning, and conversation flow optimization
Debug, test, and document AI and voice pipelines
Collaborate with engineering teams to implement AI features end-to-end
Primary Skills
Required Skills & Hands-On Knowledge
Strong understanding of Artificial Intelligence fundamentals
Working knowledge of Large Language Models (LLMs) and their applications
Hands-on experience using OpenAI APIs or similar LLM frameworks
Practical exposure to Voice AI systems (STT, TTS, conversational flows)
Experience building LLM + voice-based projects or prototypes
Basic proficiency in Python and API-based development
Secondary Skills (Good To Have)
Familiarity with NLP concepts and text processing
Exposure to prompt engineering and conversational design
Awareness of real-time voice pipelines and audio processing
Understanding of cloud-based AI deployments
What We're Looking For
Candidates who have built LLM or voice-based projects, not only theoretical knowledge
Strong curiosity, ownership, and willingness to experiment
Ability to learn fast and work independently
Good communication and documentation skills
What You'll Gain
Hands-on experience with LLM and Voice AI systems
Mentorship from experienced AI engineers
Exposure to production-grade AI workflows
Opportunity for full-time conversion based on performance
Strong foundation in applied AI engineering
