About Ambitio: Copilot for Education Abroad

At Ambitio, we’re building India’s first AI-powered global admissions platform, designed to make one of life’s most complex decisions simpler, smarter, and more accessible.

Our mission is to democratize access to top-tier global education by replacing guesswork, bias, and expensive consulting with data-driven, personalized AI guidance.

Founded by IIT BHU alumni and backed by First Cheque, BLinC Invest, and We Founder Circle, we are a product-led company where AI is not a feature, it’s the core.

The Brain: Our AI engine is trained on 10M+ data points and 1M+ successful applications, delivering predictive Admit Probability scores
The Ecosystem: From LLM-powered Essay Optimizers to advanced RAG pipelines and recommendation systems
The Impact: 40,000+ students guided to admits from Stanford, Oxford, NYU, and the Ivy League

We’re now scaling our AI systems to support the next million users.

About the Role: AI Engineering Intern

Most AI internships stop at prompt engineering. This one doesn’t.

We’re looking for AI Engineering Interns who want to move beyond notebooks and experiments and work on real, production-grade AI systems used by thousands of users. This is not a “learn and observe” role. This is a build, optimize, and deploy role. You’ll function as a high-ownership AI engineer, contributing directly to the core intelligence layer of the product.

What you’ll work on

You’ll work on real-world AI problems that go far beyond basic LLM usage:

Production AI Systems : Build, optimize, and deploy models that serve real users (not just local notebooks)
RAG Pipelines & Retrieval Systems : Design high-accuracy, low-latency retrieval systems for complex decision-making
Agentic Workflows : Build autonomous AI systems capable of reasoning over messy, unstructured data
Model Optimization : Experiment with fine-tuning techniques (PEFT, prompt tuning, etc.) to improve output quality and reliability
Predictive Modeling : Improve the algorithms behind Admit Probability for highly competitive universities

Why this role matters :

This is one of those rare opportunities where:

The impact is real → Your models directly influence life-changing decisions
The system is broken → Admissions today is chaotic, biased, and opaque
The opportunity is massive → We’re building the intelligence layer for a $10B+ problem
Every model you improve:

helps a student make a better decision
reduces uncertainty in a high-stakes journey
and unlocks opportunities they didn’t know existed

If you want to build AI that actually ships and matters, this is it.

What makes you a great fit?

Must-haves:

Strong ML/DL fundamentals (you understand how models work, not just APIs)
Solid grasp of DSA, probability, and system thinking
Proficiency in Python
Hands-on experience with PyTorch / TensorFlow / Scikit-learn

Bonus:

Experience with RAG systems, LangChain, or LLM pipelines
Familiarity with vector databases (Pinecone, Milvus, etc.)
Kaggle, research work, or open-source contributions

Mindset:

You’re a builder, you learn by doing, not waiting
You care about shipping working systems, not just experiments
You enjoy debugging complex issues and figuring things out
You take ownership of outcomes, not just tasks

Don’t apply if

You need constant guidance and a highly structured environment
You prefer theoretical research over shipping real systems
You’re looking for a “safe” internship primarily for brand value

How you’ll contribute

Own AI features end-to-end: from experimentation → deployment
Ship production-grade models used by thousands of users
Build and improve intelligent systems (RAG, agents, recommendations)
Debug and optimize models in real-world conditions
Work closely with founders and core engineers
Continuously improve performance, accuracy, and reliability

What your day will look like

No isolated experiments. No toy problems. A typical day might include:

Turning ambiguous AI problems into structured solutions
Building and deploying models into production
Debugging model failures or hallucinations
Improving retrieval quality or response accuracy
Collaborating with engineers and founders on product decisions
Shipping fast, testing, and iterating

How to apply :

Share your resume with us. Show us what you’ve built.

Share your GitHub / ML project / deployed system
Walk us through your approach and decisions
Help us understand how you think

Hiring Process

We keep it fast, focused, and meaningful:

R1: Intro Call → Background, projects, and curiosity
R2: Tech Round → ML fundamentals + problem-solving + system thinking
R3: Founder Round → Ownership, ambition, and builder mindset

Offer

If there’s a strong match:

You’ll receive a quick decision and fast offer rollout
You’ll join as a high-ownership AI intern (not a support role)
Exceptional performance can lead to a full-time AI Engineer offer

AI Intern