Computer Vision Engineer

MilTech 🪖

Overview

We are seeking a highly skilled and experienced Senior/Lead Computer Vision Engineer specializing in Navigation to join our innovative R&D team. In this pivotal role, you will drive the development and deployment of state-of-the-art computer vision algorithms for autonomous navigation systems, contributing to our efforts in robotics, autonomous vehicles, drones, or similar fields. You will work cross-functionally with engineering, product, and research teams to deliver robust, real-time solutions that enable safe and intelligent navigation in dynamic environments.


Responsibilities

  • Lead the design, development, and optimization of computer vision algorithms for localization, mapping, and navigation.
  • Develop and implement algorithms for object detection, segmentation, SLAM, 3D scene reconstruction, visual odometry, and sensor fusion (using cameras, LiDAR, IMUs, etc.).
  • Guide the integration of computer vision modules with navigation and control systems, ensuring seamless operation in real-world conditions.
  • Collaborate with software, hardware, and product teams to define requirements and deliver scalable, robust navigation solutions.
  • Stay current with advancements in deep learning, computer vision, and robotics, and introduce relevant state-of-the-art techniques into the product.
  • Design and execute experiments to evaluate performance and robustness; analyze results and iterate on solutions.
  • Prepare technical documentation, progress reports, and presentations for internal and external stakeholders.


Requirements

  • 5+ years of experience in computer vision, preferably in navigation, robotics, or autonomous systems.
  • Master’s or PhD in Computer Science, Robotics, Electrical Engineering, or related field.
  • Strong proficiency in Python and/or C++.
  • Hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and classical computer vision libraries (e.g., OpenCV, PCL).
  • Experience in deploying and optimizing models for single-board computers such as Raspberry Pi, Nvidia Jetson
  • Proven track record of developing and deploying real-time vision algorithms for navigation tasks in challenging environments.
  • Extensive knowledge of SLAM, visual odometry, sensor fusion, and related algorithms.
  • Experience with ROS, embedded systems, and real-time software development is a plus.
  • Excellent problem-solving skills, strong analytical mindset, and effective communication abilities.


Preferred Qualifications

  • Knowledge of SLAM and related models.
  • Familiarity with the MAVLink protocol and ArduPilot.
  • Familiarity with edge computing or real-time GPU-based inference.
  • Publications or contributions to the open-source community in vision or robotics.
Published 5 June
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