Teams at Laelaps AI

Own reliability and test infrastructure for autonomous security robots, including release pipelines, GPU-backed simulation, regression suites, hardware-in-the-loop testing, failure injection, reproducibility tooling, and measurable acceptance gates. Convert field incidents into permanent tests and ensure only validated builds reach customer robots. Partner with autonomy engineers across perception, localization, planning, and locomotion while managing cloud infrastructure and test systems.

Develop multi-agent reinforcement learning and orchestration algorithms for cooperative autonomous robot surveillance. Work includes decentralized decision-making, task allocation, simulation, optimization, benchmarking, and deployment on real quadruped robots. The role involves researching, implementing, evaluating, and comparing learning-based and classical planning approaches for scalable, robust multi-robot coordination.

Build and scale simulation infrastructure for robotic digital twins. Develop pipelines that convert lidar maps into simulation-ready environments, create reinforcement learning training environments, generate rare-event scenarios, model RGB, thermal, and lidar sensors, and measure and reduce sim-to-real gaps. The role also involves GPU-parallel simulation and collaboration with robotics, orchestration, reliability, and test infrastructure engineers.