Vetted dbt Professionals

“Data engineering / ML practitioner with experience at MetLife building transformer-based sentiment analysis over large unstructured datasets and productionizing pipelines with Airflow/PySpark/Hadoop (reported 52% efficiency gain). Also implemented embedding-based semantic search using Pinecone/Weaviate to improve retrieval relevance and enable RAG for customer support and document matching use cases.”

“ML/NLP practitioner who built a retrieval-augmented generation (RAG) system for large financial and operational document sets using Sentence-Transformers (all-mpnet-base-v2) and a vector DB (e.g., Pinecone), with a strong focus on retrieval evaluation and chunking strategy optimization. Experienced in entity resolution (rules + embedding similarity with type-specific thresholds) and in productionizing scalable Python data workflows using Airflow/Dagster and Spark.”

“Backend engineer with Morgan Stanley experience building and owning an end-to-end Python FastAPI microservice for high-volume market data used by trading and risk systems. Strong in performance tuning and reliability (PySpark, Redis caching, async APIs), real-time streaming with Kafka, and production operations (Docker/Kubernetes, GitOps-style CI/CD, monitoring). Has led cloud/on-prem migration work across AWS and Azure, including fixing Azure Synapse performance issues via query and pipeline redesign.”

“AI/ML Engineer who built a production RAG-based LLM system for insurance policy documents, turning thousands of messy PDFs into a searchable index using LangChain, Azure AI Search vectors, hybrid retrieval, and FastAPI. Strong focus on evaluation (MRR/precision@k/recall@k, REGAS) and performance optimization (vLLM), with prior clinical NLP experience using BERT-based NER validated on ground-truth datasets.”

“Candidate states they are very familiar with the venture capital/studio/accelerator landscape and expresses strong willingness to pursue entrepreneurship "at all costs," but did not provide details on a current startup, business plan, fundraising, or prior accelerator/VC involvement during the interview.”