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Internship Program Overview

Program Objective


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AI & ML Internship for Grad Students

We are offering an exclusive internship program for graduate students in Data Science, Machine Learning, or related fields, providing them the opportunity to solve real-world AI and Machine Learning challenges.
Utilizing AXIO, our groundbreaking AI platform, participants can rapidly design AI solutions and present to industry experts, potentially leading to exciting employment opportunities.

Program Details


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10-week AI & ML Internship Program

Work on domain-specific business use cases curated by industry experts.
Use AXIO (our ground-breaking AI Platform) to automatically generate Tailored Synthetic Data and Detailed Metadata for these specific real-world business use cases.
Build a machine-learning model that utilizes this tailored synthetic data to solve the specific business use case.
Pitch to Industry Experts for a chance at securing Paid Internships or Full-time Employment.

Stage One

Initial Challenge


Candidates solve the to be eligible to apply for this internship program.
You have one-week to solve this problem and submit.

Stage Two

Interview


Qualified candidates progress to the interview stage, where we assess their problem-solving and technical skills.
We offer internship positions to selected candidates who clear this interview stage.

Stage Three

Internship


Selected interns choose from a list of real-world business use cases curated by industry experts.
Mentors provide guidance and support to help interns solve these real-world business use cases over a 8-week period.

Stage Four

Pitch


Candidates who are able to successfully solve these real-world business use case(s) get an opportunity to pitch their solutions to a panel of industry experts.
Shortlisted candidates get a chance to interview for paid internships & FTE positions.

Sample Use Case



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Cybersecurity for Card Transactions


Description: Preventing enumeration attacks on card transactions to safeguard customer data and financial assets.
Business Context: Large financial institutions struggle to protect their systems from enumeration attacks on card account numbers during authentication and authorization. These attacks probing systems to identify valid card numbers and authentication data, leading to potential cyberattacks like fraud, identity theft, and unauthorized access to sensitive information. Successful attacks can result in financial losses, reputational damage, regulatory penalties, and legal liabilities.
Key Result: Increase the detection rate of enumeration attacks by 50%, improving from a detection rate of 60% to 90% within the next quarter.

Why Us?


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Intern at an exciting early-stage AI startup working on cutting edge Gen AI and AutoML powered solutions.


Potential Employment: Solve business problems relevant to hiring leaders, improving your chances for potential employment.


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