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Ramtin Khorrami
Principal Software Engineer specializing in AI/ML and cloud-native backend systems
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McKinsey data/ML practitioner who led production deployment of an entity resolution + semantic search platform for unstructured finance and healthcare data, integrating with legacy systems under HIPAA constraints. Deep hands-on stack across transformers (spaCy/HF BERT), embeddings + FAISS, and production MLOps/workflow tooling (Airflow, Docker, CI/CD, Prometheus/Grafana), with reported gains of +30% decision speed and +25% search relevance.
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Key Strengths
- Led entity resolution system for unstructured finance and healthcare data
- Deployed fine-tuned transformer models (BERT) to production on AWS/Azure with MLOps practices
- Improved decision-making speed by 30% via better data organization/linking
- Reduced entity resolution errors by 20% using clustering and active learning with manual + automated validation
- Improved semantic search relevance by 25% using embeddings + FAISS vector search
- Production-grade Python workflow engineering (Airflow, Docker, CI/CD, monitoring/observability)
- Legacy system integration via API-based architecture with regulatory constraints (HIPAA)
- Strong evaluation discipline (precision/recall/F1, MRR, top-k, A/B testing)
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