Jack Griffin

Freelance Software Engineer | Machine Learning Specialist

London, UK.

About

Highly accomplished Freelance Software Engineer and Machine Learning Specialist with a strong academic background in Computer Science (First Class Honours). Proven ability to design, develop, and optimize full-stack applications and complex machine learning systems, driving significant improvements in performance, data integrity, and user experience. Expertise spans scalable web development, robust database solutions, and advanced ML model implementation, consistently delivering high-impact technical solutions for diverse clients.

Work

Education Services Client

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Freelance Software Engineer

London, England, UK

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Summary

Led full-stack development initiatives, integrating critical payment systems and resolving complex database migration issues to enhance platform reliability and data integrity for an education services client.

Highlights

Engineered and deployed a secure Stripe webhook purchase flow, utilizing Zod-validation and 256-bit CSPRNG tokens to ensure data integrity and collapse failure paths into a single error, enhancing system reliability.

Resolved critical PostgreSQL 63-character identifier limit issues by authoring a 521-line migration that addressed 16,463 lines of JSON schema across tables, enums, and indexes, preventing silent data truncation.

Identified and rectified a complex greedy-regex bug across 261 FK statements in 20 migration files, preventing corrupted SQL commits and maintaining database consistency.

Non-Profit Organisation

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Freelance Software Engineer

London, England, UK

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Summary

Drove the implementation of advanced Next.js routing, caching, and strict TypeScript practices, optimizing application performance and code quality for a non-profit organization.

Highlights

Developed a scalable catch-all Next.js routing solution that resolved arbitrary-depth hierarchies from a single file and pre-computed breadcrumb URLs, eliminating path traversal across 263 routes.

Implemented Next.js 16 Cache Components across 13 query modules with a custom half-hour cache profile, optimizing data retrieval and enabling dynamic page scoping via connection().

Elevated code quality and reliability by applying maximum TypeScript strictness (exactOptionalPropertyTypes, noUncheckedIndexedAccess) across 12 Payload CMS collections, eliminating type assertions.

Education

Queen Mary University of London

London, England, UK
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BSc (First Class Honours) Computer Science

CONEL

London, England, UK
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Access to Higher Education Diploma (Distinction) Computing

Languages

English

Skills

Python

TypeScript

JavaScript

SQL

FastAPI

Next.js 16

React 19

Payload CMS

Drizzle ORM

Tailwind CSS 4

PostgreSQL

pgvector

Redis

Stripe

Vercel

Git

Statistics

convex analysis

matrix calculus

cross-validation

regularisation

Projects

Machine Learning Approaches to Sparse Data in Financial Index Tracking

Summary

BSc Dissertation focusing on advanced machine learning for financial index tracking, specifically addressing sparse data challenges.

aclue - ML Recommendation Platform

Summary

Architected and built a full-stack ML recommendation platform designed for personalized content delivery and optimized performance.