Mid-level Machine Learning Engineer specializing in MLOps, NLP, and production ML systems
Machine Learning Engineer5 years experienceMid-LevelTelecommunicationsMedia & EntertainmentConsulting
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About
Backend/founding-engineer-style builder who designed and evolved a near-real-time customer churn prediction platform (FastAPI + AWS SageMaker/Lambda + Redis + MLflow) to enable real-time retention actions, reporting ~18% churn reduction. Demonstrates strong production engineering in secure API design, incremental migrations with data integrity safeguards, and robustness improvements in async pipelines (idempotency, DLQs, retry visibility).
Experience
Machine Learning EngineerComcast
Machine Learning EngineerDeloitte
Education
University of Central Missourimaster, Computer Science
Aurora’s Technological & Research Institutebachelor, Computer Science and Engineering
Key Strengths
Designed near-real-time churn prediction platform with low-latency, reliable architecture
Delivered measurable business impact: ~18% churn reduction via real-time personalized retention actions
Production ML platform engineering (model serving, versioning/rollback with MLflow, AWS deployment)
API reliability and frontend enablement via strict validation (Pydantic) and versioned, predictable contracts (OpenAPI)
Security-by-default approach (JWT/OAuth, least privilege, rate limiting, secrets management, RLS)
Led low-risk backend migration using parallel run, feature flags, incremental rollout, and data integrity validation (checksums/shadow reads/backfills)
Identified and mitigated async retry/partial-failure edge cases using idempotency keys, tighter transactions, DLQs, and observability
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