I’m a C++ Systems / Backend Engineer expanding into Data Science, Machine Learning, AI, and AI-defense systems.

My background is in building things close to the metal — C++ systems, game engine architecture, real-time networking, backend APIs, simulations, and performance-focused software. Now I’m combining that with Python, pandas, SQL, ML, risk analytics, and AI engineering to move toward work in fintech, quant/risk analytics, machine learning engineering, and defense-oriented AI systems.

I like working where performance, architecture, data, and real-world problem-solving meet.

“Learning never stops — so you might as well enjoy the ride.”

My core strength is C/C++ systems development, especially in environments where performance, reliability, and architecture matter.

I’m currently building skills across two connected tracks:

• C/C++ Systems Programming – understanding how software works under the hood
• Networking – TCP/UDP, real-time communication, backend services, and low-latency systems
• Game Engine Architecture – rendering, memory, tooling, and engine structure
• Linux Development – working close to the OS and understanding system behavior
• Performance Optimization – profiling, bottlenecks, and clean system design

• Python for Data Science – pandas, NumPy, data cleaning, notebooks, and analysis
• SQL & Databases – querying, filtering, aggregation, and structured data workflows
• Machine Learning Foundations – scikit-learn, regression, classification, evaluation, and feature engineering
• Fintech / Risk Analytics – portfolio risk, expected value, credit-risk toy models, and market data analysis
• AI Defense & Security Exploration – AI safety, adversarial thinking, detection systems, and robust ML pipelines

I care about clean architecture, maintainability, and writing code that frankly AI and my seniors — won’t hate.(No promises tho)

A custom C++ game engine built from scratch. Focused on modular architecture, OpenGL rendering, clean engine structure, and CMake/Linux-based workflows.

What it shows: Graphics pipeline understanding, engine architecture, low-level systems thinking, and C++ design.

A real-time public transport delay prediction system built during HackYeah.

I worked on the C++ backend, designing APIs, handling route/delay data, and powering real-time map visualization alongside a cross-functional team.

What it shows: Real-time systems, backend architecture, routing logic, and practical networking.

Multiplayer systems development for a 21-person game project. I helped design and implement networked gameplay systems and core mechanics.

What it shows: Teamwork, multiplayer architecture, game networking, and production-style collaboration.

A data project using football match data from online CSV sources.

The project explores reading data from URLs, cleaning columns, combining datasets, and analyzing match results using pandas.

What it shows: Data ingestion, pandas workflows, real-world CSV handling, filtering, grouping, and sports analytics.

A planned hybrid project combining my C++ background with Python data science.

The idea is to build a C++ simulation engine that generates portfolio/risk scenarios, exports results to CSV, and uses Python/pandas for analysis, visualization, and reporting.

Planned features:

• C++ portfolio simulation engine
• CSV export pipeline
• Python analytics layer
• Value at Risk / drawdown / volatility calculations
• Risk dashboard or notebook report

What it will show: C++ systems engineering + Python analytics + fintech/risk modeling.

I’m also beginning to explore AI-defense-oriented projects, including:

• ML model monitoring
• anomaly detection
• adversarial input awareness
• AI misuse detection concepts
• robust data pipelines
• security-focused AI tooling

Goal: Build practical projects that combine systems engineering, machine learning, and security-minded thinking.

C++ • C • Python • C# • Rust basics • Go basics

Python • pandas • NumPy • SQL • SQLite • matplotlib • scikit-learn

Linux • Git • CMake • TCP/UDP networking • APIs • multithreading basics • profiling

Unreal Engine • Unity • OpenGL • ImGui • Rider • Visual Studio • CLion

Machine Learning • Data Science • Quant/Risk Analytics • AI Defense • MLOps basics • Linux networking

I’m currently pushing deeper into:

• 🐍 Python for Data Science and ML
• 📊 pandas, NumPy, SQL, and data cleaning
• 🤖 scikit-learn and beginner machine learning projects
• 💰 Fintech, quant, and risk analytics
• ⚙️ Modern C++ and performance-focused design
• 🌐 Linux networking and backend systems
• 🛡️ AI defense, robust ML systems, and security-aware AI tooling

The goal is simple:

Build production-grade technical projects that combine systems engineering, data, ML, and real-world problem solving.

Lately, I’ve been especially interested in:

• AI defense and ML security
• Machine learning engineering
• Risk analytics and financial modeling
• Data-driven backend systems
• Asynchronous networking patterns
• Low-level Linux behavior
• Scalable backend architectures
• C++ + Python hybrid applications

Basically: how to build software that stays useful, fast, and reliable under pressure.

I’m working toward roles and projects around:

• Machine Learning Engineering
• Data Science / Data Analytics
• Fintech Engineering
• Quant / Risk Analytics
• Backend / Systems Engineering
• AI Defense and Security-Oriented ML Systems

My long-term goal is to become the kind of engineer who can build both:

1. The system that runs fast and reliably, and
2. The intelligence layer that learns from data and supports decisions.

I’m always open to collaborating on backend, systems, game technology, data science, ML, or AI-defense-oriented projects — especially the kind that make you think a little harder.

📩 LinkedIn: https://www.linkedin.com/in/swastik-t-8aa131168/ 🔗 Explore more of my work right here on GitHub.