Summary
David González is an AI Engineer with 10 years of experience, currently at Neptune North, who blends machine learning research, software engineering and production infrastructure to deliver scalable, versioned and monitorable ML systems. Previously at Twilio he led cross-team efforts to evaluate and serve STT, NLP and LLM models, built a production RAG service on OpenSearch, and created a generic ML evaluation pipeline that reduced on-call incidents. He is skilled in Kubernetes, Istio, Python asyncio, Temporal and ML tooling (SageMaker, scikit-learn, KServe), and has a strong academic foundation with bachelor’s and two master’s degrees from Universidad Carlos III de Madrid. David’s work sits at the intersection of model quality and operational reliability—he favors reproducible, traceable pipelines that make advanced models dependable in production. An early researcher in applying deep generative and autoencoder techniques to synthetic road imagery and LiDAR-based perception, he brings both experimental rigor and hands-on engineering to complex AI deployments.
10 years of coding experience
4 years of employment as a software developer
Charles III University of Madrid (Universidad Carlos III de Madrid)
Spanish, English