Machine Learning Engineer

📋 Description Build and own underwriting ML infrastructure. Real-time quotes API layer for low-latency serving. Train models on tens of millions of patients and hundreds of millions of claims. Ensure training is reliable, reproducible, scalable as data grows. Enable data scientists and actuaries to test ideas quickly. Own end-to-end production infrastructure with SLAs and monitoring. 🎯 Requirements Strong track record building ML/data infra in production at scale. Proficiency in Python; comfortable with large datasets (Spark/Databricks). Experience with model training pipelines and low-latency serving. Experience building tooling that makes others faster (experimentation, backtesting). Ability to own end-to-end systems with SLAs, monitoring, on-call. Genuine interest in modeling and hands-on data work. 🎁 Benefits High ownership from day one. Impact on healthcare access and lives at scale. Growth, expansion, and fast career velocity. Apply AI to a problem that matters in healthcare. High pace, collaborative team environment.