Summary
Basil Ihuoma is a Machine Learning and MLOps engineer with nine years of experience building and productionizing data-driven systems from Lagos, Nigeria. He has designed IaC-backed distributed processing platforms using Apache Spark and Delta Lake, and implemented end-to-end ML workflows with Kubeflow, KFServing and model monitoring. At Turing and Hamoye he focused on pipeline development and scalable deployment patterns that bridge data engineering and ML operations. His background includes hands-on time-series forecasting, feature engineering, and automated monitoring from early-career data science roles through senior MLOps responsibilities. Continuously learning—he holds nanodegrees in Cloud DevOps and distinctions in scientific computing—Basil combines practical cloud-native tooling with a curiosity-driven approach summarized on GitHub as “learning to build, building to learn.” He brings a pragmatic focus on observability and reproducibility that makes experimental models reliably production-ready.
9 years of coding experience
5 years of employment as a software developer
ALX-T Cloud DevOps Engineer, Nanodegree, ALX-T Cloud DevOps Engineer, Nanodegree at Udacity
Scientific Computing and Python for Data Science, Data Science, Distinction, Scientific Computing and Python for Data Science, Data Science, Distinction at WorldQuant University
Bachelor of Technology - BTech, Information Management Technology, Bachelor of Technology - BTech, Information Management Technology at Federal University of Technology, Owerri.