Software Engineering Intern · Bitquark
Jan 2026 — PresentBuilding the frontend of a macOS productivity app from first commit to launch.
Mathematics · Quantitative Finance · ML
It’s always mathematical.
I study Mathematical Finance and Applied Mathematics at Waterloo, with a focus on machine learning.
I build systems that survive contact with the real world.
I grew up in Botswana, where I ranked first nationally out of more than 37,000 candidates and received the Presidential Award, before moving to Canada for Waterloo. Studying the same problems across two very different academic cultures is what makes the thinking richer.
The curiosity hasn’t changed since I first got hooked on coding — only the toolkit has. These days I work where quantitative finance meets machine learning, and I write research code with the same discipline I picked up shipping software to real users.
Building the frontend of a macOS productivity app from first commit to launch.
Core engineer on an AI voice companion, shipped across web and iOS.
A quantitative spread-trading platform across all 8 North American power markets — regime detection, ML forecasting, and a Monte Carlo risk engine.
An agentic research loop that reads finance papers, extracts factor hypotheses, and writes the code to test them against decades of market history.
A chess engine that learns: a custom ResNet with policy and value heads, trained on millions of grandmaster games and paired with Monte Carlo Tree Search.
A browser-based, audio-first tour guide that narrates location-specific facts in real time, routing you through a city as it talks.
Ask a database questions in plain English and get back SQL or MongoDB queries, with explanations. Schema-aware and multi-database.
Search research papers by meaning, not keywords — natural-language queries over a corpus using deep-learning embeddings.
Ranked 1st nationally in Botswana out of 37,629 BGCSE candidates.