About the job
At FieldAI, we are revolutionizing the way robots engage with the real world. Our innovative Machine Learning team based in Seattle develops risk-aware, dependable, and field-ready AI systems that address the most challenging problems in robotics, unleashing the full potential of embodied intelligence. We adopt a practical methodology that transcends standard, purely data-driven techniques or transformer-exclusive architectures, merging state-of-the-art research with real-world applications. Our solutions have achieved global deployment, and we consistently enhance model performance through rapid refinements driven by actual field use.
We are on the lookout for a talented Staff AI Software Engineer specializing in Edge Model Optimization & Deployment. In this pivotal role, you will take the lead in optimizing, integrating, and deploying our machine learning models onto real robotic platforms. You will be responsible for the entire edge inference stack, including profiling and accelerating models, enhancing runtime performance across latency, throughput, memory, and power consumption. Collaborating closely with perception, autonomy, and platform teams, you will ensure the delivery of robust on-robot behavior in real-world environments. You will set the technical direction, elevate engineering standards, and guarantee that our models operate efficiently and reliably on constrained hardware in diverse settings.
This is a unique opportunity to influence the future of robotic autonomy by converting cutting-edge machine learning into high-performance, production-ready edge deployments that function reliably within complex, dynamic environments on actual robots.
