Hammad
Ahmad

I'm an AI/ML engineer with an MSc (Merit) in Applied Artificial Intelligence and Data Analytics from the University of Bradford and a first-author Springer paper. My work sits where applied research meets production: measuring a system honestly, then making it fast enough to put in front of real users.

Right now I build and run Jobzyl on my own: a live job search aggregator over 29 integrated sources and a 4.2M+ row Postgres index, with semantic CV-to-posting matching in pgvector. The half I care about is what it refuses to say. Pay renders in the period the employer quoted or not at all, and a posting that names no recognised skill reports as too thin to score rather than as a confident 0%.

Before that, at Outlyst, I cut mean call latency 54%, from 2.4s to 1.1s across 2,100+ calls, by profiling async I/O and restructuring connection pooling. For my dissertation I built FinLaw-UK, a graph-augmented RAG system for UK financial regulation where a Neo4j knowledge graph resolves every citation before the answer ships, and refuses rather than answer when it cannot. After submitting, I re-measured my own evaluation and found two of the reported figures were regex shape-checks rather than correctness measures; I published the correction and a report on which numbers reproduce.

I'm interested in roles where I can keep pushing that boundary - semantic search and retrieval at scale, LLM infrastructure, or high-throughput ML systems.