Norbert Health is hiring an Applied AI Engineer

We're looking for an Applied AI Engineer to take our growing collection of foundation models and ML components from manually run, sometimes locally trained workflows to fully automated, production-grade MLOps pipelines: deployed reliably on robots in nursing facilities. We need someone who knows the model landscape cold, treats evaluation as a first-class engineering problem, and has strong opinions about when to prompt, RAG, fine-tune, swap, or buy. You’ll work across cloud and edge deployments, and some of the systems you’ll touch are on a SaMD pathway, so you’ll need to be comfortable shipping under regulatory constraints. Integrate foundation models and ML components (VLMs, LLMs, ASR/TTS, detection/segmentation, embeddings) into our production pipelines, using both open-weight models and third-party APIs. Build RAG and agent-style orchestration for clinical reporting and conversational interfaces. Ship real-time streaming pipelines (voice agents) alongside batch and request-response workloads. Build evaluation harnesses that catch regressions across model swaps and measure performance against clinical-grade accuracy targets. Fine-tune and retrain models (LoRA, PEFT, supervised fine-tuning) using data collected from our deployed fleet. Deploy across our inference surfaces: third-party APIs, self-hosted, and on-robot edge. Build the data flywheel: pipelines that collect, label, version, and feed production data back into model improvement. Partner with the algorithms team (signal processing, computer vision) on integration with their lower-level pipelines.