Applied AI Engineer

About the role

We are seeking an Applied AI Engineer to join our team and help us automate and improve our production pipelines. This role involves integrating various foundation models and ML components into our systems, building robust evaluation frameworks, and deploying these solutions in real-world nursing facilities.

Responsibilities

• Integrate foundation models and ML components into our production pipelines
• 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 to catch regressions and measure performance against clinical-grade accuracy targets
• Fine-tune and retrain models using data collected from our deployed fleet
• Deploy across our inference surfaces including 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 on integration with their lower-level pipelines

Requirements

• BS in Computer Science, Engineering, or a related field, or equivalent hands-on experience
• 4+ years shipping ML/AI systems in production outside of academic settings
• Strong working knowledge of the modern foundation model landscape (open-weight LLMs and VLMs, common detection/segmentation backbones, embedding models)
• Hands-on experience with PEFT/LoRA and supervised fine-tuning
• Strong Python; comfortable with the deployment toolchain (ONNX, quantization, at least one inference runtime—TensorRT, vLLM, llama.cpp, etc.)
• Experience with a cloud ML training/MLOps platform (GCP Vertex AI, AWS SageMaker, Azure ML, or equivalent)
• Ability to work independently, solve complex problems, and drive projects to completion
• Edge ML deployment (Jetson, ARM, mobile NPUs)
• Real-time voice AI pipelines (STT, TTS, streaming LLM)
• Production RAG systems beyond toy implementations
• Medical devices, SaMD, or other regulated ML environments
• MLOps tooling (Weights & Biases, MLflow, DVC, etc.)
• Active learning or human-in-the-loop labeling workflows
• C++ for integrating with our computer vision pipeline

Qualifications

• Real impact: your code provides care for patients today
• High autonomy and technical ownership—you’ll define how we operate AI in production
• Work at the intersection of cutting-edge AI, edge computing, and healthcare
• A talented, excellent, diverse and international team
• Equity participation in the company’s future
• Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing
• Transparent, mission-driven culture focused on continuous learning
• Competitive salary and equity