Freelance AI & Machine Learning Fraud Detection Job

“Apply and see what happens!” — This mindset is the biggest mistake for this job

Whenever people see an AI job post, one thought immediately comes to mind:

“Let me just apply and see what happens.”

For this job, that mindset can be your biggest mistake.

In today’s digital world, securing financial transactions has become one of the toughest challenges. If you work with AI and Machine Learning, you’ve probably already noticed that traditional fraud detection models are no longer enough. Hackers are now actively trying to deceive AI systems themselves using adversarial attacks.

Recently, Guires Solutions Private Limited announced a freelance researcher position focused on AI & Machine Learning for Adversarial Financial Fraud Detection.

If you’re planning to build a career in this space—or are thinking of applying for this role—this post will serve as a complete, practical guide for you.

Who is this job really for?

This is not a basic data entry role or a routine coding job.

It’s a high-level academic research + implementation-driven role.

This position is ideal for you if:

You are a Master’s or PhD researcher

If you’re currently doing advanced research in AI, Cybersecurity, or Data Science, this is a strong opportunity—especially if you’re aiming for Scopus-indexed journal publications.

You have hands-on experience in Adversarial Machine Learning

This job isn’t just about building models. It’s about understanding how models fail under attack and designing mechanisms to defend against data poisoning and adversarial manipulation.

You work with Transformers and Reinforcement Learning

If you think Transformers are only for chatbots, think again.

This role involves applying Transformer architectures to tabular data and integrating Reinforcement Learning (RL) to build adaptive defense layers.

You have 2–4 years of relevant experience

Candidates who have handled multiple end-to-end research projects and worked with large datasets like IEEE-CIS Fraud Detection will find this role most suitable.

Ask yourself these 3 questions before applying

Before applying to any serious AI research role, self-evaluation is critical. For this job, these three questions matter the most:

1. What AI tools will I use in this job?

This is a technically demanding project. You’ll primarily work within the Python ecosystem.

Key tools include:

PyTorch or TensorFlow (mandatory)

Transformer models for tabular data (e.g., TabTransformer, FT-Transformer)

Reinforcement Learning libraries such as Stable Baselines3 or Ray RLlib

Pandas and NumPy at an advanced level for data manipulation

If these tools sound unfamiliar, this role may not be a good fit—yet.

2. Have I actually used these tools before?

Have you ever:

Simulated label flipping or backdoor attacks on a dataset?

Designed an RL agent with proper reward engineering to identify poisoned transactions?

If your answer is “yes,” you’re on the right track.

If not, this role will be extremely challenging because it demands PhD-level research output, not just theoretical knowledge.

3. Can I prove this on my CV?

This is the most important question.

Saying “I know Transformers” isn’t enough.

Do you have:

A GitHub repository
A published paper
A reproducible research project

…that clearly demonstrates your work with these techniques?

Without verifiable proof, surviving a research-heavy role like this is very difficult.

Core challenges and responsibilities of the role

This position covers a wide scope. Key responsibilities include:

Working with the IEEE-CIS Fraud Detection dataset

A large, highly imbalanced dataset where feature engineering plays a critical role.

Simulating adversarial attacks

You’ll need to think like an attacker—intentionally poisoning training data through controlled adversarial strategies.

Building a hybrid defense system

Develop a Transformer-based fraud detection model integrated with an RL-driven adaptive defense layer that can adjust dynamically to attacks.

Documentation and publication

Since this is a research role, you’ll be responsible for delivering a Scopus-ready dissertation or research paper.

Compensation and work structure

Pay: Starting from ₹10,000 per month

Work type: Freelance / Part-time / Remote

Contract duration: Initially 1 month

My honest advice:

The pay may feel low compared to the skill level required. However, if you’re a student or researcher looking to add a high-impact research project to your CV, this opportunity can be extremely valuable.

Final thoughts

AI-powered fraud detection is no longer just about prediction—it’s a battlefield.

One side is constantly attacking, and the other side (you) must defend.

If you enjoy solving complex problems, experimenting with adversarial ML, and securing real-world financial systems through code, this role is worth applying for.

📞 Contact (as per job listing): Gray – 95661 33822

Freelance AI & Machine Learning Adversarial Financial Fraud Detection Guires Solutions Private Limited.

We don’t just list AI jobs — we clearly explain who each job is actually meant for.