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AI Intern (LLMs and Voice AI) 6 months(Onsite)
Job Location:
Monthly Salary:
Posted:
31 July 2026 (17 days ago)
Posted:
Application Deadline:
28 October 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Job Title: AI Intern (LLMs and amp; Voice AI)
Internship Duration: 6 Months
Employment Type: Internship (Full-Time)
Work Mode: Onsite (Work from Office)
Location: Brookfield Bangalore
Stipend: 15000 per month
Conversion Opportunity: Performance-based Full-Time Role
Eligibility
Engineering students / recent graduates from or 2027 batches
Branches: Computer Science IT AI and amp; 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
Required Skills and amp; Hands-On Knowledge
Primary Skills
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 Were 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 Youll 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
