AI/ML Intern – 2026 Batch

Job Description

Job Title: AI/ML Intern

Location: Bengaluru, India

Number of Openings: 10

Duration: 6 Months

Company Overview:

IAI Solutions (https://www.iaisolution.com/) operates at the edge of applied AI where foundational research meets real-world deployment. We craft intelligent systems that think in teams, adapt with context, and deliver actionable insight across domains.

Were currently seeking passionate and skilled AI/ML Interns who are eager to contribute to real-world AI development, have hands-on experience with model fine-tuning, and are adept in prompt engineering. If you&aposre ready to work on impactful projects and expand your expertise in AI, wed love to hear from you.

Position Summary:

As an AI/ML Intern, you will work with state-of-the-art AI technologies to design, build, and deploy intelligent systems. The ideal candidate will have strong proficiency in Python, Flask or Fast API and OOP, with real-world experience in prompt engineering, finetuning and Hugging Face, LangChain.

Key Responsibilities

- Build FastAPI endpoints that integrate LLMs in a seamless inference pipeline.
- Apply prompt engineering techniques to optimize different LLM-based applications.
- Work with advanced frameworks like LangChain, LangGraph, Hugging Face, OpenAI, and others for model inference and orchestration.
- Develop tools and implement tool calling techniques to enhance LLM capabilities.
- Use Pydantic models to enforce structure and parse LLM responses effectively.
- Leverage object-oriented programming (OOP) principles to write scalable and reusable code.
- Contribute to internal documentation and actively share findings, utilities, and best practices.
- Stay updated with the latest AI research and tooling, integrating innovations into real-world systems.

Requirements

- Must be a B.Tech Graduate of 2026 batch.
- Strong experience in Python for AI/ML development and backend systems.
- Practical knowledge in prompt engineering and LLM optimization for real-world use cases.
- Proficiency with LangChain, LangGraph, Hugging Face Transformers, and Datasets libraries.
- Background in AI/ML research or academic projects, with hands-on model experimentation.
- Solid grasp of Object-Oriented Programming (OOP) and strong problem-solving abilities.
- Ability to work independently as well as within a collaborative team environment.
- Strong communication and documentation skills to convey complex ideas effectively.

Preferred Qualifications

- Previous experience in academic or industrial research/project focused on Large Language Models (LLMs).
- Proven track record of successful AI LLM model deployments and optimizations in production or experimental settings

Perks

- Hands-on experience with real-world AI deployments.
- Work with state-of-the-art AI tools and platforms.
- Mentorship from top AI engineers and researchers.
- Flexible, innovation-driven work culture.
- Stipend: 25,000/month.
- Full-time Opportunity: Outstanding performers may be offered a full-time role as an AI/ML Engineer with a package of up to 15 LPA.

Selection Process:

Step 1: Application Submission

- Visit our Career Page
- Fill in the required details and upload your resume

Step 2: Task Assignment (24 Hours Deadline)

- Download the AI/ML Assignment from the Career Page
- Complete and submit within 24 hours
- Record and attach a 2-minute video explaining your solution (mandatory)

Step 3: Review & Shortlisting

- Our technical team will evaluate your assignment submission
- Candidates with outstanding performance will be shortlisted for interviews

Step 4: Interview

- Showcase your technical and problem-solving abilities
- Highlight your prior work, research, and understanding of AI/ML principles

Step 5: Onboarding

- Post a successful interview, well welcome you aboard Get ready to dive into exciting projects and contribute to the field of AI.

Compensation:

- Stipend: 25,000/month
- Full-Time Opportunity: Up to 15 LPA (based on performance)

How to Apply:

Apply directly via our Career Portal

Ensure submission includes:

- Updated Resume
- Project Portfolio or GitHub (if available)
- Completed Assignment + Video explanation of 2 minutes

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