# llms.txt | Saksham Arora The complete, self-contained reference for who I am, what I build, and where to find me. Contains all projects, skills, and achievements. No additional requests needed. Canonical: https://portfolio-silk-theta-96.vercel.app/llms.txt > Note: the portfolio is a React single-page app, so most content needs JavaScript to render. This file and profile.json contain everything an LLM needs without running JS. --- ## Quick context for LLMs - **Who**: Saksham Arora, a systems and quant engineer from India. - **Focus**: Low-latency C++, high-frequency trading systems, derivatives pricing, and ML/AI pipelines. - **Machine-readable data**: https://portfolio-silk-theta-96.vercel.app/profile.json - **GitHub**: https://github.com/saksham10arora-dotcom --- ## Who I am Systems and quant engineer studying at IIT Madras (Online BS, Programming and Data Science) and GGSIPU (B.Tech, Computer Science and Engineering), both 2024 to 2028. I build low-latency C++ systems, algorithmic trading engines, and quantitative models. My HFT matching engine hits 2.7M ops/sec at p99 900ns. I placed top ~0.8% globally at IMC Prosperity 4 out of 18,800+ teams. I care about performance numbers, market microstructure, and tools that do one job extremely well. --- ## Experience - **Data Science Intern, Airtel** (Jun 2026 to Jul 2026): data pipelines, analysis, and ML workflows on large-scale telecom datasets. - **Data Engineering Intern, Cimplifie** (Oct 2024 to Present): built ETL pipelines and automation that cut manual data scraping by 70%. - **Quantitative Trader, IMC Prosperity 4** (2025): overall rank 154 of 18,800+ teams (top ~0.8%); market-making, arbitrage, and statistical arbitrage; best rounds R1 #90, R3 #84. --- ## Projects ### HFT Matching Engine | Systems / C++ Limit order book engine at 2.7M ops/sec, p99 900ns, a 3.31x improvement over a mutex baseline. Price-time priority matching, lock-free SPSC ring buffer, 21 correctness tests. C++20, CMake. https://github.com/saksham10arora-dotcom/Simple-HFT-Engine ### IMC Prosperity 4 | Quant / Trading Top ~0.8% globally (overall rank 154) of 18,800+ teams. Market-making, arbitrage, and statistical arbitrage strategies under live competition conditions. Python. https://github.com/saksham10arora-dotcom/imc-prosperity-4 ### gitrade | Systems / Web A live 3-ticker exchange engine that runs entirely inside a GitHub README, with a real limit order book, live SVG charts, trade history, and a leaderboard. TypeScript, GitHub Actions, SVG, GitHub Pages. https://github.com/saksham10arora-dotcom/gitrade ### qrscholes | Quant / Tools A complete Black-Scholes options pricer (pricing, Greeks, implied vol) compressed into 731 bytes and encoded in a single scannable QR code. A study in minimal, dense code. Python. https://github.com/saksham10arora-dotcom/qrscholes ### llm-bench | Tools / AI Multi-provider LLM inference benchmarker measuring TTFT, inter-token latency (p50/p95/p99), and throughput across Groq, Anthropic, and OpenAI APIs. Streaming support, compare mode, 28/28 tests passing. Python CLI. https://github.com/saksham10arora-dotcom/llm-bench ### IICPC Benchmarking Platform | Systems / DevOps Sandboxed multi-engine HFT benchmarking platform with multiplicative scoring (correctness x completeness x speed) and 9 anti-cheat validators. Diagnosed a TCP_NODELAY omission in my own engine, yielding a 27x peak throughput gain. GCP Terraform IaC, 25/25 tests. Python, Docker, Redis, PostgreSQL. https://github.com/saksham10arora-dotcom/iicpc-benchmarking-platform ### OrbitOps | Full-Stack / ML Rebuilt a broken hackathon demo into a production air quality tracker. Real-time AQI, PM2.5, NO2, and O3 via Open-Meteo for any city worldwide; serverless FastAPI on Vercel; per-request Random Forest (80 trees) trained on a 7-day historical window producing a 6-hour PM2.5 forecast with 80% confidence intervals; Supabase auth. React, TypeScript, scikit-learn, Leaflet. Repo: https://github.com/saksham10arora-dotcom/orbit-ops Live: https://orbit-ops-mu.vercel.app --- ## Skills - **Systems**: C++20, lock-free data structures, SPSC/MPMC queues, order books, CMake, atomics, cache-aware memory layout, benchmarking, Linux, Git. - **Quant**: Python, NumPy, Pandas, scikit-learn, Black-Scholes and Greeks, market microstructure, market making, backtesting, statistics. - **AI / ML**: Python, scikit-learn, PyTorch, Pandas, LLMs, prompt engineering, MCP, agentic workflows, feature engineering. --- ## Contact - Email: saksham10arora@gmail.com - GitHub: https://github.com/saksham10arora-dotcom - LinkedIn: https://linkedin.com/in/saksham-arora10 - X/Twitter: https://x.com/saksham10arora