Computer Vision Engineer

Mentee Robotics is redefining humanoid automation with an AI-first approach, integrating cutting-edge perception, reasoning, and dexterous manipulation into a fully autonomous humanoid robot that continuously adapts and learns. Our flagship product, Menteebot v3, is designed to seamlessly integrate into industrial, logistics, and retail environments, performing complex tasks with human-like adaptability.

We are looking for an experienced Computer Vision Engineer to join our team. This role is central to our perception and autonomy stack. You will design, implement, and optimize computer vision pipelines for real-time robotic applications, ensuring the highest level of performance and reliability.

Responsibilities:

• Design, develop, and implement robust computer vision pipelines for object detection, segmentation, tracking, and 3D perception, primarily using Python/C++.
• Develop, optimize and integrate state-of-the-art models like Segmentation, Detectors and Foundation models into our real-time robotics platform.
• Work extensively with various camera interfaces (e.g., GMSL, MIPI and HSB) and sensor data to extract meaningful information for navigation and manipulation.
• Integrate and test perception components within the ROS2 framework.
• Optimize vision pipelines for low-latency, high-throughput execution on embedded or edge platforms.

Requirements:

• 5+ years of experience as a Computer Vision Engineer, Robotics Software Engineer, or ML Engineer focused on Perception.
• Extensive experience and strong proficiency in Python and C++ – a must-have (strong engineering skills are required).
• Deep understanding and hands-on experience with core computer vision concepts and libraries (e.g., OpenCV, PyTorch/TensorFlow).
• Proven experience working with advanced vision models (e.g., Segmentation, Detectors and Foundation models).
• Experience with robotic operating systems (ROS 2) and sensor integration.

Advantages:

• Experience with multi-modal data (e.g., fusing camera, LiDAR, and IMU data).
• Experience with containerization and orchestration (Docker, Kubernetes).
• Deep understanding of Linux and system-level performance optimization.
• Experience with GPU programming (e.g., CUDA).