This senior machine learning engineering role within Anduril's Frontier Systems team focuses on developing reinforcement learning policies for legged robotic platforms used in defense and industrial settings. The position involves designing and training locomotion algorithms in GPU-parallelized simulations, creating terrain curricula to ensure robustness in unstructured environments, and managing the full sim-to-real transfer pipeline for physical deployment. Key responsibilities include optimizing policies for stair climbing and rough terrain traversal while collaborating with perception and manipulation engineers to integrate mobility into a complete autonomy stack. The role appeals to candidates seeking high-impact work where reliability is critical for operational success in contested environments. It offers the opportunity to solve complex robotics challenges with a small, high-performing team and requires eligibility for a U.S. security clearance.
