Computer Vision Engineer

One of our clients, an innovative deep-tech startup in the field of robotics and autonomous systems, is looking to hire a Perception Algorithm Engineer to join their R&D team. The company develops cutting-edge robotic platforms for inspection and maintenance in complex industrial environments. Their proprietary technology leverages advanced navigation, computer vision, and real-time control systems to operate autonomously in GPS-denied, harsh environments — such as maritime infrastructure, energy facilities, and other challenging terrains.

Position Overview

As a Perception Algorithm Engineer, you will play a key role in developing and implementing the core 3D perception algorithms that power the company’s autonomous capabilities. You will work on multidisciplinary challenges involving sensor fusion, 3D reconstruction, depth estimation, and real-time scene understanding, integrating your solutions into robotic systems operating in the field.

Key Responsibilities

• Design and implement advanced algorithms for 3D perception, including Reconstruction, Depth Estimation, Object Detection & Tracking, and Scene Understanding.
• Process and fuse data from multiple sensors (LiDAR, stereo/RGB-D cameras, IMU, GNSS).
• Optimize algorithms for real-time performance and deploy them on embedded and robotic platforms.
• Collaborate closely with navigation, control, and hardware teams to deliver an integrated end-to-end perception system.
• Conduct simulations, field experiments, and benchmarking to validate accuracy, robustness, and scalability.

Requirements

• B.Sc./M.Sc. (Ph.D. preferred) in Computer Science, Electrical/Computer Engineering, Applied Mathematics, or a related field.
• Proven experience in Computer Vision / 3D Perception, including Reconstruction, SLAM, Depth Estimation, or Multi-View Geometry.
• Strong background in Machine Learning / Deep Learning with 3D applications (Point Clouds, Meshes, Neural Radiance Fields – NeRF).
• Proficiency in Python and C++ (CUDA experience is a plus).
• Hands-on knowledge of relevant libraries and tools (PyTorch/TensorFlow, OpenCV, PCL).
• Practical experience with advanced sensing systems (LiDAR, stereo / Time-of-Flight cameras).
• Ability to thrive in a multidisciplinary environment, bridging algorithms, software, and hardware.