Mustafa Kasap is a senior engineering leader with 20+ years of experience who currently leads development of an AI-powered enterprise compliance platform from Redmond, WA. He has a track record of building LLM-native knowledge systems, MLOps pipelines, and near-real-time analytics at scale—most recently shipping a multi-source discovery service indexing millions of records and an internal compliance MVP in ~10 weeks. Known for end-to-end ownership, he combines architecture, roadmap, and operational readiness with rigorous reliability practices like SLOs, runbooks, and regression/telemetry-driven improvement. He excels at cross-organizational alignment, navigating product, security, legal, and compliance constraints to enable audit-ready AI features for regulated domains. Mustafa’s background blends deep research and academic training in big data and mathematical modelling with hands-on program leadership across large and small teams. Beyond delivery, he brings a practical knack for engineering process: instituting design reviews, CI/CD discipline, and measurable throughput gains that lift team quality.
Introduction to Machine Learning and Azure Machine Learning Services. Hands on labs to show Azure Machine Learning features, developing experiments, feature engineering, R and Python Scripting, Production stage, publishing models as web service, RRS and BES usage
Contributions:24 commits, 3 PRs, 20 pushes in 4 years 11 months
Contributions:9 pushes, 1 branch in 3 years 6 months
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