Vita

Last updated: 03/06/2025

Summary: Seeking engineering roles in AI/ML. I have a strong foundation in mathematics coupled with advanced programming ability. This enables me to quickly iterate on and implement complex ideas. I am naturally optimistic, an effective team player, a quick learner, and possess high stamina.

Here is some illustrative work, see my GitHub, projects page, and blog for more.

1. gevals (demo/repo): TypeScript eval framework for comparing LLM configurations, featuring automated audio dataset generation with noise overlay, parallel processing via BullMQ, and CLI tooling. Implemented comprehensive evaluation metrics for latency, cost, and accuracy using LLM critics.
2. Waymo Scene Generator (demo/repo): Download 1k shards of the Waymo Open Motion Dataset, train a small Conditional Variational Autoencoder to sample 5s future trajectories.
3. Lean Agents (animation/demo/repo): Developed a multi-agent system in Lean 4 where autonomous agents collaborate to solve mathematical theorems by working on sub-lemmas. Implemented a decentralized architecture where agents publish and build upon each other's solutions.

Notable achievements: Qualified for MENSA; Finished 1st in Class in both undergraduate and MSc.

Technical Skills

• Languages: Python, TypeScript, SQL, R
• Packages, Frameworks: Chroma, PGVector, React.js, Next.js, FastAPI, Django, PyTorch, AWS, Docker, Git, CI/CD, LLM APIs, LangChain
• Expertise: RAG, evals, AI and ML theory

Experience

AI Engineer (contract). Scytale Digital. June 2025 -.
Developing an AI investment thesis and running weekly AI tutorials for the team.

AI Engineer. Aipolabs. Jan 2025 - Apr 2025.
Designed, implemented, and tested a "Guardrails" feature to prevent irrelevant, harmful, or undesirable agent behaviour. Built and documented the internal evals suite for continuous testing of AI features.

AI Engineer (contract). sea.dev. Nov 2024.
Built a multi-turn dialogue eval measuring LLM extraction accuracy, assess tone and user-friendliness (published on arXiv).

Data Scientist. Barrows Global. May 2019 - Aug 2019.
Cleaned and extracted features from major retailer's data, built models to analyse and draw inference on the sales performance in the store environment to inform the advertising strategy for clients.

Actuarial Intern. Old Mutual Limited. Feb 2017.
Performed Value at Risk (VaR) modelling and worked with the reinsurance team to rectify a database error which produced duplicate policy holders.

Education

PhD in Mathematical Statistics. University of Warwick. Oct 2020 - Aug 2024.
Developed training algorithms for large data sets, and methods for debiasing logistic regression in high dimensions. See more here.

MSc in Statistics. University of Warwick. Oct 2019 - Sep 2020.
Winton Award (Finished 1st in class)

BCom in Actuarial Science. University of Cape Town. Feb 2015 - Nov 2018.
STA4006W Class Medal (Finished 1st in class)