Principal HFT & AI/ML Engineer

A highly experienced professional with 21 years in HFT, algo trading, and quantitative finance, now also specializing in AI/ML engineering. Holds a University of Tokyo degree and is a DASCA Certified Principal Data Scientist. Proven track record in building DMA/HFT options trading engines (kernel-bypass, lock-free hot paths), FPGA-accelerated Monte Carlo pricers, and extensive numerical libraries. Formerly held positions as Head Quant and CTO. On the AI/ML front, expertise includes CUDA/C++ inference, PyTorch pipelines, federated learning, quantum circuit models (PennyLane/Qiskit), time-series classification, and synthetic data generation. Has re-implemented a SIGGRAPH paper in CUDA/C++ for scene reconstruction and developed a real-time pose streaming system. Public projects include Thetis26 (C++20 lock-free data structures, formally verified), rust-secure-memory (post-quantum KEM, encrypted enclaves), notbbg (Go real-time market data terminal), and gpu-backtest (Rust/CUDA/Metal backtesting engine). Open to roles in trading systems, HFT infrastructure, AI/ML engineering, quantitative research, and systems programming, available for both contract and and permanent positions.