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Brian Gomez
Senior Machine Learning Engineer specializing in AI/ML, NLP, and computer vision
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About
McKinsey & Company ML/NLP practitioner who builds production-grade AI systems across sectors (notably healthcare and finance), including RAG/LLM solutions, entity resolution pipelines, and embedding-powered search with vector databases. Demonstrated measurable impact (40% reduction in data duplication) and strong MLOps/data workflow practices (Airflow, MLflow, Spark, AWS/GCP, Prometheus, CI/CD).
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Key Strengths
- Designed and deployed ML/NLP systems (including RAG with LLMs/Transformers) to connect disparate datasets
- Entity resolution pipeline using blocking + XGBoost with rigorous metric-based validation (precision/recall/F1) and manual review for healthcare
- Achieved 40% reduction in data duplication via data cleaning/entity matching approach
- Improved search relevance and data linking using embeddings (BERT, GPT-4) with vector DBs (Pinecone, FAISS)
- Built scalable, production-grade Python workflows using Airflow, Spark, AWS/GCP with monitoring (Prometheus) and CI/CD
- Balanced rapid prototyping with production delivery using agile iteration and performance gates
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