Vilota develops spatial perception products for autonomous and tele-operated robotic systems, focusing on lightweight sensor hardware, advanced vision-based software, and reliable operation in indoor and outdoor environments.
We bridge cutting-edge research with production-ready systems, transforming theoretical algorithms into reliable products deployed in real operating environments.
We are looking for curious, mathematically strong engineers or scientists who enjoy solving difficult problems and translating ideas into robust implementations.
Job Scope
- Research, develop, and improve visual localisation and visual-inertial odometry (VIO) algorithms.
- Design and implement state estimation, sensor fusion, and nonlinear optimisation algorithms for robotics applications.
- Develop mathematical models for cameras, IMUs, and other perception sensors, including calibration and error modelling.
- Investigate challenging localisation failures and develop practical solutions for robustness under real-world conditions.
- Apply machine learning and classical computer vision techniques where appropriate to improve perception performance.
- Design experiments, analyse datasets, and evaluate algorithm performance using quantitative metrics.
- Prototype new algorithms in Python or C++, and optimise them for deployment in production systems.
- Collaborate with hardware and software engineers to integrate algorithms into embedded and robotic platforms.
- Stay current with the latest research in computer vision, robotics, state estimation, and machine learning, and evaluate their applicability to company products.
Required Qualifications
- Bachelor's or Master's degree in Math, Computer Science, Robotics, Electrical Engineering, or a related field.
- Proficiency in programming languages such as Python, C++, or Rust.
- Strong understanding of sensor technologies (e.g., cameras, IMUs) and SLAM techniques.
- Experience with perception frameworks and libraries (e.g., ROS, OpenCV, Eigen, GTSAM).
- Solid knowledge of machine learning and computer vision algorithms
- Familiarity with 3D point cloud processing and geometric reasoning
Desirable Qualifications
- Experience deploying perception systems on drones, autonomous robots, or embedded platforms.
- Experience with camera and IMU calibration.
- Familiarity with deep-learning frameworks such as PyTorch or TensorFlow.
- Exposure to software optimisation for resource-constrained or real-time environments.
- Experience reading, implementing, or reproducing algorithms from academic research papers.
