Alex Fafula

Directed machine learning systems and GPU infrastructure for Poland's statutory credit bureau, managing on-premises hardware clusters and model serving runtimes. Built low-latency inference pipelines running private open-source models in an isolated, air-gapped banking network.

Advised 15+ international technology clients on migrating from commercial LLM APIs to self-hosted open-source inference stacks on private cloud and bare-metal GPU infrastructure. Benchmarked and optimized inference runtimes across various hardware configurations, achieving up to 65% reduction in cloud compute costs.

Led edge telemetry and low-level software engineering across Diversey's global fleet of 1,200 autonomous industrial cleaning robots. Deployed real-time anomaly detection models directly on edge microcontrollers and embedded Linux gateways.

Governed reference architectures for enterprise data platforms, machine learning workloads, and cloud environments across 90,000+ employees in 180 countries. Directed modernization of high-throughput analytics platforms on Databricks and cloud environments.

Taught post-graduate and MBA courses covering High-Performance Computing, Compiler Design, Machine Learning Architectures, and Applied Econometrics.

Architected real-time bidding algorithms and programmatic audience segmentation systems processing billions of events daily with sub-50ms latency SLAs. Built distributed Kubernetes clusters and model serving infrastructure with automated health checks and traffic shifting.

Architected high-throughput big data processing engines and real-time fraud detection systems on Cloudera Hadoop for tier-1 commercial banks and telecom operators. Built M.A.I.A., an interactive NLP assistant for automated profile evaluation and recruitment screening.

Architected high-throughput ingestion and NLP pipelines analyzing millions of global news and social records daily for the Thomson Reuters / LSEG MarketPsych Indices used by Wall Street quant funds. Designed low-latency string parsing, sentiment extraction, and market entity disambiguation algorithms.

Doctoral dissertation awarded with honours; computational modeling of decision-making under uncertainty. Formally recognized with an academic award by the Scientific Society for Economic Informatics (NTIE).

Rigorous 5-year quantitative program spanning high-performance computing, compiler design, software engineering, and applied statistics.