CS @ Georgia Tech building AI/ML and software systems — with a side interest in quantitative trading.
I like building systems that actually run end to end — LLM/RAG applications, evaluation tooling, and the occasional always-on trading bot. Currently looking for AI/ML & software engineering internships/co-ops (Fall 2026).
| Project | What it is | Stack |
|---|---|---|
| JavaDocRAG | Retrieval-augmented Q&A over the JDK 25 API docs — hybrid BM25 + dense retrieval, cross-encoder reranking, cited answers | Python · FastAPI · FAISS · Claude |
| kalshi-latency-arb | Async latency-arbitrage system for the CFTC-regulated Kalshi event-contract exchange — quarter-Kelly sizing, risk controls, backtester | Python · asyncio · WebSocket |
| ibkr-dual-ema-trading | Session-aware Dual-EMA crossover trading system for Interactive Brokers — real-time bars, order-lifecycle management, risk controls, Telegram control, backtester | Python · ib-insync · asyncio |
| llm-guided-evolution | Research (GT VIP lab) — LLM inference optimization within the Guided Evolution LLM + genetic-algorithm NAS framework; quantization, RAG, distributed runs on PACE/SLURM | Python · PyTorch · SLURM/HPC |
- Software Engineering Intern @ OpsNerve.ai — built an LLM-powered root-cause-analysis agent (prompt pipelines + evaluation harness) for an AIOps incident platform.
- Undergraduate Researcher, GT VIP (Automated Algorithm Design) — LLM quantization and RAG-retrieval experiments inside an evolutionary-algorithm framework, running distributed jobs on Georgia Tech's PACE HPC cluster (SLURM).
- Personal projects — RAG systems and quantitative/automated-trading infrastructure (see pinned repos).
Python · Java · C · SQL · JavaScript
ML/AI: PyTorch · RAG pipelines · LLM evaluation · quantization · scikit-learn
Systems: Linux · SLURM/HPC · Docker · Git · SQLite · REST APIs
- LinkedIn: sri-palani
- Email: sririthishpalani@gmail.com