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Pradeep Nadella
Mid-level AI/ML Engineer specializing in LLM optimization and real-time fraud/risk modeling
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About
ML engineer with 5 years at Stripe building and productionizing real-time fraud detection at massive scale (3M+ transactions/day; $5B+ annual payment volume). Delivered measurable impact (22% accuracy lift, 18% loss reduction, +3–5% authorization rates) and has strong MLOps/orchestration experience (Docker, Kubernetes, Airflow, MLflow, CI/CD, monitoring/rollback) plus a structured approach to LLM agent/RAG evaluation.
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Key Strengths
- Built and deployed real-time fraud detection models at Stripe at very large scale (3M+ transactions/day; $5B+ annual payment volume)
- Improved fraud detection accuracy by 22% and reduced losses by 18%
- Optimized low-latency, high-throughput inference pipelines with batching/caching and Kubernetes-based scaling
- Production ML operational excellence (containerization, orchestration, monitoring, CI/CD, rollback)
- End-to-end ML pipeline orchestration with Airflow (ingestion → features → training → evaluation)
- Strong evaluation discipline for LLM/agent workflows (offline benchmarks, edge-case testing, hallucination/latency metrics, human feedback)
- Effective cross-functional collaboration with risk analysts and compliance; translated fraud patterns into ML features
- Balanced fraud prevention with customer experience (increased authorization rates by 3–5%)
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