Open to opportunities

brandy buck

@brandybuck

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Software engineering student building scalable backend, distributed systems, and ML solutions.

India

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What I'm looking for

I’m looking for a role where I can build scalable backend and distributed systems, write robust developer-friendly tooling, and apply ML for real-world optimization—growing through strong engineering mentorship and end-to-end ownership.

I’m a Software Engineering undergraduate with strong interests in backend engineering, systems programming, distributed systems, and developer tooling. I’ve built projects and ML solutions that focus on scalability, deterministic behavior, and maintainable architecture.

As an AI Intern, I built machine learning solutions in Python using Scikit-Learn for predictive analytics, including preprocessing, feature engineering, model evaluation, and hyperparameter tuning, plus reusable ML pipelines and documentation. My projects span distributed systems (like a lightweight etcd-inspired store with leader election and Raft concepts), information retrieval using Tantivy and PostgreSQL, multimedia streaming with Rust and FFmpeg, and AI-driven QoS management for 5G networks.

Experience

Work history, roles, and key accomplishments

Machine Learning Intern

Unified Mentor Pvt. Ltd.

Feb 2025 - Apr 2025 (2 months)

Designed and evaluated supervised learning models on real-world datasets using exploratory data analysis, feature engineering, and model optimization. Implemented modular Python code for training, evaluation, and inference with standard ML metrics and documentation practices.

Python Supervised Learning Machine Learning Feature Engineering Optimization Model Training Model Evaluation Inference Documentation Metrics

Artificial Intelligence Intern

Knack Tech E-Learning Pvt. Ltd.

Dec 2024 - Feb 2025 (2 months)

Built machine learning solutions in Python using Scikit-Learn for predictive analytics, including preprocessing, feature engineering, model evaluation, and hyperparameter tuning. Developed reusable ML pipelines and documented experimental findings while collaborating on end-to-end AI workflows.