Open to opportunities

Ruber Bernardoni

@ruberbernardoni

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Software developer combining data science and offensive security through machine learning and reverse engineering.

Peru

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What I'm looking for

I’m looking for a role where I can build full-stack products while applying machine learning and offensive security—doing binary reverse engineering, vulnerability research, and deploying data-driven models in the cloud.

I’m a self-taught software developer with a background in Systems and Computer Engineering (UNASAM) and about 3 years of hands-on experience across software development, data science, and offensive security. I build with the mindset of a competitor—learning fast, testing relentlessly, and turning curiosity into working solutions.

I’m passionate about Machine Learning, Big Data, and reverse engineering, and I stay sharp through active participation in CTFs (CTFtime, Hack The Box, TryHackMe, pwn.college, HackerRank) and data science competitions on Kaggle. I combine competitive programming with vulnerability analysis, binary reverse engineering, and full-stack development, from exploitation to forensics workflows.

In security work, I analyze malware and systems using tools like Autopsy, Ghidra, Cutter, radare2, and objdump, and I approach web challenges with Burp Suite, OWASP ZAP, and ffuf plus automation in Python requests and curl. In data science projects, I build and deploy models using TensorFlow and PyTorch with Pandas/NumPy, experimenting across Google Cloud, AWS, and Microsoft Azure.

Experience

Work history, roles, and key accomplishments

Competitive Programming & Software

Personal Projects / Unasam

Developed applications and algorithms for competitive programming and built full-stack web applications using multiple frameworks. Also created smaller projects in Godot and experimented with WebAssembly.

Competitive Programming C++Java Python Full Stack Web Development Django Flask Spring Boot Godot WebAssembly

Data Science Competition Participant

Kaggle

Built machine learning and deep learning models for Kaggle competitions, including data cleaning, analysis, and visualization. Deployed and experimented with models using major cloud platforms.

Machine Learning Deep Learning TensorFlow PyTorch Data Cleaning Data Analysis Data Visualization Pandas NumPy AWS

Capture The Flag (CTF) Competitor

CTFtime

Solved binary exploitation, reverse engineering, digital forensics, and web hacking challenges on CTF platforms, including malware analysis and vulnerability exploitation. Used tools such as Ghidra and Autopsy, and web testing tools like Burp Suite and OWASP ZAP.