Autonomy Software Engineer - Mapping and Localization

About UCR

UCR (Under Control Robotics) builds multipurpose robots to support human workers in the world's toughest jobs—turning dangerous work from a necessity into a choice. Our work demands reliability, robustness, and readiness for the unexpected—on time, every time. We're assembling a mission-driven team focused on delivering real impact in heavy industry, from construction and mining to energy. If you're driven to build rugged, reliable products that solve real-world problems, we'd love to talk.

Position Overview

At UCR, building robots is a team sport. As a Robotics Autonomy Engineer, you'll take ownership and lead the development of autonomy systems that power our multipurpose robots across diverse and unstructured environments. You'll design, implement, and optimize cutting-edge localization, mapping, navigation, and SLAM systems—including advanced techniques such as 3D Gaussian Splatting—that enable our robots to perceive, understand, and act in the real world with confidence.

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
• Ability 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)