Artificial Intelligence Intern

Artificial Intelligence Intern | Trensor AI

About Trensor AI

At Trensor AI, we’re building the next generation of agentic AI frameworks — systems that can reason with structure, learn with clarity, and act with awareness.

Our mission is to bring discipline, reliability, and explainability to autonomous reasoning — starting with domains like compliance automation , where logic matters as much as intelligence itself.

We are looking for 4 AI / ML Engineer Interns who are eager to explore the frontiers of structured intelligence and reasoning systems.

Role :

AI / ML Engineer Intern — working on research and development of agentic AI workflows, reasoning systems, and orchestration architectures under mentorship from the founding team.

Responsibilities :

• Design and implement agentic AI workflows using LangChain, LangGraph, and related orchestration frameworks
• Experiment with RAG pipelines, LLM-based reasoning, and multi-agent coordination
• Build integrations across data pipelines, backend systems, and microservices
• Collaborate with the founding team on research, design, and architecture decisions
• Explore how AI can act with awareness, not just automation

Qualifications

Job Type :

Unpaid Internship (Learning-focused opportunity)

Compensation

This is currently an unpaid internship.

Outstanding interns may receive a performance-based stipend or paid full-time opportunity at the end of the internship.

All interns will receive certification, mentorship, and access to the IIT deeptech ecosystem.

Location

Remote (no relocation or travel required)

Why Join Us

Application Details :

If you’re excited about how intelligence can be structured and reasoned, we’d love to hear from you.

Please send your resume or a short note about your interest in agentic AI to :

📧 trensorai@gmail.com

About Trensor AI

Trensor AI is a deeptech startup focused on building structured, explainable, and agentic AI systems. We believe AI should reason as well as it learns — combining the precision of logic with the power of learning .