FieldAI is transforming how robots interact with the real world. Our growing ML team in Seattle builds risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence. We take a pragmatic approach that goes beyond off-the-shelf, purely data-driven methods or transformer-only architectures, combining cutting-edge research with real-world deployment. Our solutions are already deployed globally, and we continuously improve model performance through rapid iteration driven by real field use.
We are seeking an accomplished Staff AI Software Engineer - Edge Model Optimization & Deployment to drive the optimization, integration, and deployment of our ML models on real robotic platforms. In this role, you will own the edge inference stack end to end, profiling and accelerating models, improving runtime performance across latency, throughput, memory, and power, and partnering closely with perception, autonomy, and platform teams to deliver robust on-robot behavior in the field. You will set technical direction, raise engineering rigor, and ensure our models run efficiently and reliably on constrained hardware across diverse environments.
This is an opportunity to shape the future of robotic autonomy by translating state-of-the-art ML into high-performance, production-grade edge deployments that operate reliably in complex, dynamic environments on real robots.