Summary
Emeka Ama is an MLOps engineer based in London with nine years of experience building and productionizing ML systems across startups and scale-ups. He has delivered end-to-end pipelines and low-latency model deployments—from document similarity and custom NER used by thousands of customers to transaction classifiers and LLM evaluation infrastructures handling millions of logs weekly. Emeka combines hands-on model optimization (ONNX/TensorRT, pruning), cloud-native deployments (Kubernetes, ArgoCD, GCP/AWS), and CI/CD automation to shrink workflows from days to seconds. His work has measurably improved business metrics (e.g., legal product retention >80%) and supported large customer bases (hundreds of thousands of users). A pragmatic engineer and developer advocate, he also creates content and tooling to scale team knowledge and reproducible ML practices. Less obvious: he’s published research and packaged a dynamic embedding topic model to analyze parliamentary bills across multiple African countries.
9 years of coding experience
5 years of employment as a software developer
Bachelor's degree Computer Science, Bachelor's degree Computer Science at ESAE University, Benin Republic