Jorge Quiroga

Senior Machine Learning Engineer with 11+ years of experience designing and deploying enterprise-scale Generative AI platforms, LLM-powered applications, and intelligent information retrieval systems. Career progression from backend and data engineering at Rackspace Technology and Axonius into specialized AI/ML engineering at Google and Dropbox, where the focus shifted to production-grade Natural Language Processing, Retrieval-Augmented Generation (RAG), and agentic workflows. Deep expertise across the full lifecycle of search and retrieval systems — from embedding generation, vector search, and ranking to LLM orchestration with LangChain and LangGraph, model serving with vLLM and SGLang, and low-latency inference optimization using TensorRT-LLM and ONNX Runtime. Supporting breadth includes Python, PySpark, SQL, distributed data pipelines, and cloud-native architecture on AWS (SageMaker, EKS, ECS, Lambda, Step Functions, Glue), containerized with Docker and orchestrated on Kubernetes. Complementary skills span MLOps (CI/CD, monitoring, observability, model lifecycle management), responsible AI guardrails, and enterprise knowledge integration. Consistently delivers high-relevance, low-latency AI systems that drive measurable improvements in user engagement and operational efficiency, while working collaboratively across cross-functional teams.