Autonomy Software Engineer - Mapping and Localization
Noble Machines · Sunnyvale, CA · 1 wk ago
EngineeringFull-time
Responsibilities
- Develop and maintain real-time mapping, localization, and navigation software for mobility robotic systems
- Build scalable SLAM pipelines using a mix of sensors, including LiDAR, vision, and IMU
- Implement 3D scene representations using cutting-edge techniques such as 3D Gaussian Splatting, NeRFs, and other neural or volumetric methods
- Integrate localization and mapping modules with motion planning and control systems
- Deploy robust autonomy stacks to on-board compute platforms and validate them in both simulation and real-world testing
- Analyze and tune performance of perception and SLAM systems in challenging environments
- Collaborate with mechanical, electrical, and software engineers to develop co-designed autonomy solutions
- Write clean, modular, production-quality code with thorough documentation and testing
- Operate and support robots during field testing and customer deployment
Requirements
- 4+ years of experience working in robotics, autonomy, or a closely related field
- Strong foundation in SLAM, probabilistic localization, 3D reconstruction, and navigation algorithms
- Deep experience with C++ and Python, especially in real-time robotics or embedded systems
- Experience building and deploying autonomy stacks using frameworks such as ROS or ROS2
- Proven ability to develop algorithms for sensor fusion and state estimation (e.g., EKF, UKF, particle filters)
- Hands-on experience with real robot systems—ground, legged, or aerial platforms
- Familiarity with 3D mapping techniques including voxel grids, mesh reconstruction, and Gaussian Splatting
- Demonstrated rapid growth and technical ownership on complex autonomy projects
- Able to prioritize and execute tasks in a fast-paced, dynamic environment
- Excellent communication and collaboration skills across disciplines
Nice to Have
- Experience with GPU-accelerated vision or perception pipelines (CUDA, TensorRT)
- Exposure to deep learning-based SLAM, view synthesis, or scene understanding techniques
- Experience with multirobot SLAM, loop closure, or graph optimization frameworks
- Contributions to open-source robotics or perception libraries
- Comfort debugging hardware/software integration in field settings
- Experience with autonomy in unstructured or GPS-denied environments
- Strong understanding of simulation frameworks (e.g., Gazebo, Isaac Sim, Unity Robotics)