Job Description

Role Overview: As a Senior ML Engineer at Ping, you will sit at the intersection of research and data engineering—designing, training, and deploying ML models powering our property attribute classification, document extraction, and geospatial products. This hands-on role requires reading a paper in the morning, prototyping an idea by lunch, and shipping it to production by end of week. You will own ML systems end-to-end: from data pipeline design and feature engineering through model training, evaluation, and production deployment. The role is remote-friendly, with the option to work onsite at our Miami, FL office. Responsibilities: Design, train, fine-tune, and evaluate ML models (LLMs, classification, sequence models) for property insurance. Build and maintain robust data pipelines that feed training, evaluation, and inference workloads at scale. Develop rigorous evaluation frameworks—establish metrics, build rater alignment processes, and apply statistical methods to determine when a candidate model is genuinely better than production. Run controlled experiments, ablations, and A/B tests; communicate findings clearly with appropriate uncertainty quantification. Deploy models to production and own their performance, drift monitoring, and iteration cycles. Collaborate with the engineering team to integrate ML services into our backend (Django/Python) and frontend (React/TypeScript) products. Stay current with the ML literature and translate relevant advances into practical improvements for our products.