Summary
Ricardo Soares is a Machine Learning Engineer with nine years' experience building production ML systems, currently applying his expertise at Meta in London. He blends data science and software engineering to design scalable pipelines and services, from real-time event processing and knowledge graph enrichment to bank transaction forecasting and NLP-driven merchant detection. Ricardo has repeatedly moved teams from monoliths to microservices, implemented Kafka- and Airflow-based ingestion flows, and managed analytics databases (Redshift, Citus) with automated data-quality alerts. He’s delivered end-to-end solutions such as live transcription and entity tagging for Zoom calls and an object-relational mapping layer to streamline data scientist workflows. Comfortable across cloud environments and containerized architectures, he pairs hands-on Python engineering with a formal AI background (MSc, First-Class) and a track record of translating research-grade models into reliable production services. An underappreciated strength is his habit of building observability and test coverage into pipelines early, reducing firefighting as systems scale.
9 years of coding experience
3 years of employment as a software developer
Master of Science - MS, Artificial Intelligence, First-Class Honors, Master of Science - MS, Artificial Intelligence, First-Class Honors at University of Aberdeen
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at University of Wolverhampton
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Universidade do Algarve