EchoTwin AI is pioneering AI-driven infrastructure intelligence, redefining how cities are managed. Powered by a proprietary visual intelligence engine with full spatial reasoning, EchoTwin transforms municipal fleets into mobile urban sensorsâcreating living digital twins that provide real-time insights into infrastructure, compliance, and safety. By enabling municipalities to proactively monitor, predict, and resolve issues, EchoTwin helps build resilient, self-healing, and sustainable urban ecosystems. More than âsmart cities,â EchoTwin is advancing the era of cognizant citiesâurban environments with the awareness to see, think, and act on challenges in real time.
We are seeking a skilled Perception Engineer to join our team, specializing in the development of Simultaneous Localization and Mapping (SLAM) systems using monocular cameras. The ideal candidate will design, implement, and optimize algorithms to enable robust real-time localization and mapping for 3D construction, contributing to cutting-edge advancements in robotics and computer vision.
Design and develop monocular SLAM algorithms for real-time localization and 3D mapping in dynamic environments.
Optimize SLAM pipelines for performance, accuracy, and computational efficiency on resource-constrained platforms.
Integrate monocular camera data with other sensor inputs (e.g., IMU) to enhance system robustness.
Conduct experiments to evaluate and improve SLAM performance under varying lighting, occlusion, and motion conditions.
Collaborate with cross-functional teams, including robotics, software, and hardware engineers, to integrate SLAM solutions into production systems.
Implement and test algorithms in C++ and/or Python, ensuring scalability and reliability.
Stay updated on the latest advancements in computer vision, SLAM, and monocular depth estimation, incorporating relevant techniques into development.
Document technical designs, algorithms, and experimental results for internal and external stakeholders.
Bachelorâs or Masterâs degree in Computer Science, Electrical Engineering, Robotics, or a related field. A PhD is a plus.
3+ years of experience in computer vision, SLAM, or related perception systems.
Strong proficiency in C++ and/or Python for algorithm development and optimization.
Hands-on experience with monocular SLAM techniques, including feature detection, tracking, and loop closure.
Experience with deep learning-based approaches for monocular depth estimation or visual odometry.
Knowledge of sensor fusion techniques, particularly with IMUs or other inertial sensors.
Familiarity with computer vision libraries (e.g., OpenCV, PCL) and frameworks (e.g., ROS, Eigen).
Experience deploying SLAM systems in real-world applications, such as autonomous vehicles or drones.
Understanding of camera models, calibration, and image processing techniques.
Experience with real-time systems and optimizing algorithms for embedded platforms.
Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.
There are endless learning and development opportunities from a highly diverse and talented peer group, including experts in various fields, including Computer Vision, GenAI, Digital Twin, Government Contracting, Systems and Device Engineering, Operations, Communications, and more!
Options for medical, dental, and vision coverage for employees and dependents (for US employees)
Flexible Spending Account (FSA) and Dependent Care Flexible Spending Account (DCFSA)
401(k) with 3% company matching
Unlimited PTO
Profit sharing
Please do not forward resumes to our jobs alias, EchoTwin AI employees, or any other company location. EchoTwin AI is not responsible for any fees related to unsolicited resumes.
If you want to empower the worldâs most important citiesâand the institutions that run themâyou belong here. At EchoTwin AI, we value excellence regardless of background and are committed to building a team that reflects the communities we serve.
EchoTwin AI is an Equal Opportunity Employer. We consider all qualified applicants without regard to race, color, religion, sex (including pregnancy), sexual orientation, gender identity or expression, national origin, age, disability, veteran status, genetic information, or any other status protected by applicable law.
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