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Develop and deploy multimodal foundation models and agentic AI for multi-robot coordination. Design training recipes, curate datasets, build simulation and RL environments, evaluate performance, and integrate models into real-time robotic systems with field trials.

Lead and conduct original research in embodied AI for autonomous systems, developing and evaluating large-scale perception, decision-making, and control models. Translate research into deployed prototypes, collaborate with engineering and field teams, support field tests and data collection, and define research strategy across reinforcement learning, vision-language-action, sim-to-real, memory, and multi-agent coordination.

The Embedded Engineer will develop software for robotic platforms, architecting firmware, designing control loops, integrating software with sensors and hardware, and ensuring performance and reliability for defense applications.

Design and scale the infrastructure for Fury's AI model training and deployment, ensuring efficient data pipelines and collaboration with AI teams.

Design and build software for robotic systems, focusing on perception, autonomy, control, and infrastructure. Collaborate across teams to enhance performance and reliability.