I'm a machine learning engineer with a strong data science background (4 years professional ML, 7+ years Python). I enjoy writing Rust. I've built several Rust projects focused on understanding and building diffret types systems, from p2p blockchains to ML models trained in python and served in rust.

• is-it-slop: Detect AI generated slop using classic ML. Blazingly fast embedded model infrence, served in Rust using ONNX & a custom TFIDF vectorizer.
• Heisenberg: Complete offline location enrichment tool, using the geonames database to backfill and enrich location data.
• market-making: System for ingesting live market data streams, replicating orderbooks locally, and distributing market data to message queues and time-series databases. Focused on engineering a market-making system from the ground up.
• p2p blockchain: Basic implementation of a blockchain that runs on a p2p network to understand and implement a blockchain from scratch.
• ZK Sudoku prover: Verifying the correctness of Sudoku puzzles without ever revealing the puzzle solution itself. A simple rust base implementation of a Zero Knowledge Prover based on graph colouring.
• Typed Prompt: A simple type-safe, validated prompt management system for LLMs

• Learning how to do things I dont currently know how to do.
• Rust, async internals, atomics, locks, lower-level primitives
• Compilers & systems programming
• Building things from scratch
• Swimming, running, netball, gaming

Ideally, a role where I build fast systems in Rust.