I am a Computer Engineering graduate student at UT Dallas with professional experience in machine learning systems, distributed backend services, and real time applications. I focus on building reliable, high performance software that bridges research ideas with production ready systems.
My work spans applied machine learning, backend engineering, and systems optimization. I enjoy designing clean architectures, optimizing performance bottlenecks, and deploying scalable services.
- Open source contributions.
- Deep learning optimizations including quantization, binary neural networks, and efficient training techniques
- Large language models and multimodal learning systems
- Production grade ML deployment using Flask and FastAPI
- Quantum computing and quantum machine learning
Languages
Python, C++, Java, Rust
Deep Learning
PyTorch, TensorFlow Keras, OpenCV, Hugging Face Transformers, Scikit learn
Backend & Systems
REST APIs, WebSockets, gRPC, Flask, FastAPI, Docker, Redis
Data & Tooling
NumPy, Pandas, SQL, Git, Linux, CI CD
Quantum Computing Qiskit, Cirq, Pennylane
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Plant Disease Diagnosis
Hybrid CNN ViT based feature extraction with SVM classification, deployed as a Flask API for real time inference -
Binary Neural Networks
Custom training pipelines and optimization strategies for efficient deep learning models -
Real Time and Systems Projects
Microservices, low latency APIs, and performance focused backend systems
See individual repositories for detailed implementations and documentation.
- Portfolio: https://rahiljain1366.github.io/Portfolio
- LinkedIn: https://www.linkedin.com/in/rahil-jain-3129961b5
- Email: rahiljain1366@gmail.com
I value clean architecture, measurable performance improvements, and building systems that scale reliably.