Aravindh Bieber

I am an AI and Data Science engineer focused on designing and deploying machine learning systems that solve real-world problems. I build end-to-end solutions from data preprocessing and modeling to deployment and monitoring, with an emphasis on reliability and performance.

At App In Technology, I developed a full-stack stock trading platform with secure authentication, transaction handling, admin workflows, and Docker-based CI/CD, improving system reliability through logging and error handling. My projects include an ML-driven logistics route optimizer that reduced costs and delays and a music beats generator using multi-layer LSTMs for interactive rhythm prototyping.

I also built a real-time Indian Sign Language to text translator optimized for constrained devices using CNN+LSTM, OpenCV preprocessing, pruning and quantization, and UI feedback with confidence scores. I enjoy applying a mix of classical algorithms and modern ML techniques—Dijkstra, Clarke-Wright heuristics, regression forecasting, and deep learning—to deliver tangible impact.

I bring strong coding fundamentals (Python, Java, SQL), experience with tools like Docker and Git, and a track record of algorithmic problem solving. I seek opportunities to contribute to product-facing ML systems where I can iterate quickly, measure impact, and scale solutions.