Pre-screened and vetted.
“Built and deployed an LLM-powered financial document processing and summarization platform at Morgan Stanley using a production RAG pipeline (PDF ingestion, embedding-based retrieval, schema-constrained JSON outputs) delivered via FastAPI microservices on Kubernetes. Drove measurable impact (40% reduction in manual review time) and improved factual accuracy for numeric fields by 30% through metadata-aware retrieval, strict schemas, and post-generation validation, with a human feedback loop from financial analysts.”
“Full-stack engineer who has owned workflow-builder/editor products end-to-end, including multi-tenant graph validation platforms built with TypeScript/React and Node. Experienced designing microservices with RabbitMQ/SQS-style queues (idempotency, retries, DLQs) and building internal admin CMS tools (SvelteKit + FastAPI) that replaced manual spreadsheet processes and became the operational source of truth.”
Intern Machine Learning Engineer specializing in NLP, RAG, and time-series forecasting