We are a robotics company building autonomous systems that operate in complex, dynamic environments. Our perception stack enables our robots to understand, localize, and navigate the world in real time, and we place a strong emphasis on robustness, performance, and maintainable engineering.

We are seeking a Perception Engineer to design and implement SLAM, state estimation, and computer vision algorithms for real-world robotic systems. You will work closely with robotics, controls, and systems engineers to bring perception algorithms from research into reliable, production-ready software.

This role is ideal for someone who enjoys bridging the gap between theory and deployment—turning academic algorithms into efficient, well-engineered systems.

Responsibilities

• Design and implement SLAM and localization systems (visual, visual-inertial, lidar, or multi-sensor)
• Develop and integrate computer vision pipelines for perception tasks such as feature extraction, tracking, mapping, and scene understanding
• Implement and optimize estimation algorithms (e.g., filtering, optimization-based methods)
• Fuse data from multiple sensors (cameras, IMUs, lidars, depth sensors)
• Evaluate perception system performance using real-world data and metrics
• Optimize algorithms for real-time performance and robustness
• Collaborate with controls and planning teams to support downstream autonomy
• Maintain clean, well-tested, production-quality code
• Contribute to tooling, datasets, and evaluation frameworks

Required Qualifications

• Strong background in robotics perception or computer vision
• Experience implementing SLAM or localization systems in practice
• Solid understanding of:
• 3D geometry and coordinate transformations
• Camera models and calibration
• Feature-based and/or direct visual methods
• Probabilistic state estimation
• Proficiency in C++ and/or Python
• Experience working in Linux environments
• Familiarity with robotics software stacks (e.g., ROS / ROS 2)
• Strong debugging and data analysis skills

Preferred Qualifications

• Experience with specific SLAM frameworks (e.g., ORB-SLAM, VINS, Cartographer, GTSAM)
• Experience with lidar-based perception and mapping
• Familiarity with deep learning–based perception models
• Experience deploying perception systems on real robots
• Knowledge of GPU acceleration (CUDA, OpenCL)
• Experience with dataset curation and annotation
• Publications or research background in robotics or computer vision