Senior Applied Scientist, Navigation
Core
Architecting and delivering intelligent, safe, and scalable navigation systems for advanced robotic systems that operate alongside humans in dynamic environments.
Role type
Senior Applied Scientist (Robot Navigation)
Builds
Production-grade navigation systems for autonomous robots
Domain
Robotics, Autonomous Systems, Computer Vision, Control Theory
Deliverable
production ML models
Required skills
Learning-based planning and control, foundation models for embodied agents, model predictive control (MPC), trajectory planning, object detection, sensor fusion, 3D perception, simulation-to-real transfer, ROS/ROS2, SLAM, localization, mapping
Preferred skills
Foundation models for robotics, visual navigation, vision-language-action models, high-fidelity simulation environments (Isaac Sim, MuJoCo, Gazebo), safety-critical systems, formal verification, multi-agent coordination
Technologies
PyTorch, JAX, ROS, ROS2, Isaac Sim, MuJoCo, Gazebo
Responsibilities
Design and deploy perception algorithms (object detection, segmentation, tracking, depth estimation); lead research in computer vision and sensor fusion; drive end-to-end ownership of ML models from data to deployment; mentor junior scientists; publish research in top-tier venues; define and track performance metrics
Seniority
Senior, hands-on IC with research leadership
