Computer Vision Engineer

Twentyfour Industries

We are an early-stage startup funded by leading European VCs with the mission to build advanced small Unmanned Systems to strengthen European sovereignty and security.

What We’re Looking For

We are seeking an expert Computer Vision Engineer to act as the architect of our drone’s environmental awareness. In this role, you will move beyond basic flight algorithms to solve complex visual challenges. You will develop the visual cortex of our UAVs, enabling them to navigate unstructured environments, detect hazards, and interpret 3D space with high precision in real-time.

The day-to-day

• Design and deploy lightweight, low-latency deep learning models for 2D and 3D object detection (e.g., YOLO, SSD).
• Implement robust multi-object tracking (MOT) to maintain awareness of dynamic obstacles across frames.
• Build semantic scene understanding to distinguish traversable space, vegetation, and hard obstacles.
• Develop pipelines for depth estimation, structure-from-motion (SfM), and monocular depth cues.
• Work on occupancy grid mapping for 3D environment representation and downstream path planning.
• Implement visual odometry and SLAM to ensure precise localization in GPS-denied environments.
• Address challenging visual conditions such as glare, shadows, motion blur, and low-light scenes.
• Optimize perception models for embedded edge devices (e.g., NVIDIA Jetson Orin) using TensorRT, CUDA, and quantization (INT8).
• Balance inference speed and accuracy to achieve high frame rates with minimal end-to-end latency.
  
  

You should apply if you

• Have deep expertise in computer vision fundamentals, including epipolar and projective geometry, calibration, and photogrammetry.
• Are highly proficient with PyTorch or TensorFlow, and OpenCV.
• Write production-grade C++ and use Python effectively for prototyping and experimentation.
• Have hands-on experience with visual odometry, SLAM, or visual-inertial systems (e.g., ORB-SLAM, VINS-Mono).
• Bring a strong mathematical foundation in linear algebra, probability, filtering (Kalman / Particle Filters), and optimization.
• Enjoy translating research ideas into robust, real-world systems on constrained hardware.
  
  

Nice to haves

• Experience with sensor fusion across camera, IMU, LiDAR, or radar.
• Familiarity with ROS2 for perception and autonomy pipelines.
• Experience working with thermal / IR sensors or event-based cameras.
• Exposure to synthetic data generation for training computer vision models.
• Background in robotics, aerospace, defense, or other safety-critical systems.
  
  

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What We Offer

• Competitive salary and equity options.
• A high-impact role shaping the perception systems of next-generation UAV platforms.
• Direct influence on core autonomy capabilities, not just incremental features.
• A collaborative, ambitious, and technically rigorous startup environment.
• Flexible working conditions, with remote work and relocation support for top candidates.
  
  

About Us

Twentyfour Industries is committed to building a fair, inclusive, and high-performance workplace where people from all backgrounds can contribute and thrive. Our team brings together individuals with different perspectives, experiences, and skills to shape the future of European security and technology.

All applicants will receive equal consideration for employment regardless of gender, age, disability, ethnic or social origin, religion or belief, sexual orientation, or any other status protected by applicable European or national law.

We particularly welcome applications from individuals who are underrepresented in the technology and defense sector, including women, people with disabilities, and those from diverse cultural backgrounds.

We aim to provide a respectful, supportive, and transparent recruitment process. If you require adjustments to take part in our hiring process, please let us know so we can accommodate your needs.

If you share our mission and are motivated to work on challenges with real-world impact, we look forward to your application.