ML / AI Engineer · London, UK
I build machine-learning systems for finance and fraud.
Junior ML engineer building finance ML end to end — a credit-card fraud detector and a leakage-controlled equity ranker. Open to ML/AI roles in finance.
Selected work
Machine-learning systems across finance and computer vision, documented end to end — the problem, the approach, the tradeoffs, and honest results, including where they fall short.
A cross-sectional equity ranker: it learns to order S&P 500 stocks, turns the ranking into a risk-managed, self-explaining portfolio, and proves it with a leakage-controlled, cost-aware backtest — honest about a modest, not-yet-significant edge.
An ML + LLM prototype for stock analysis: AdaBoost signals, walk-forward validated, explained by an LLM fed structured model output so it cites rather than hallucinates — and never gives buy/sell advice.
A cascaded drone-detection system (detector → bird-verifier → type-classifier) and an IEEE paper that measures, honestly, what survives domain shift — near-perfect in-distribution scores that partly collapse on unseen data, behind a perceptual-hash leakage audit.
About
I'm Priyansh, a First-Class Computer Science graduate and junior ML engineer based in London, UK. I'm focused on machine learning for finance — fraud, risk, and the unglamorous data work that makes a model trustworthy in production.
Lately I've been building two systems end to end: a credit-card fraud detector that prices its errors in pounds, and RankAlpha, a cross-sectional equity ranker with a leakage-controlled, cost-aware backtest. I care more about honest metrics and clean pipelines than leaderboard scores.
I'm looking for an ML/AI role where I can learn from senior engineers and ship real systems — ideally at a UK fintech or bank.
Contact
I'm open to ML/AI roles and happy to talk about the work. The fastest way to reach me is email.