Senior Engineer - Visual Localisation

Role Overview

We are looking for an experienced Senior Robotics Engineer to spearhead the creation of cutting-edge visual localization systems for autonomous vehicles and robots. This role primarily focuses on crafting robust map-based localization technologies to ensure precise positioning of vehicles in intricate urban settings.

Key Responsibilities

• Create and implement algorithms to match live semantic data—such as lane marks, stop lines, road edges, and traffic elements—with vector HD map formats like Lanelet2 and OpenDRIVE.
• Build localization components that leverage Bird’s Eye View (BEV) features for spatial correlation and highly accurate vehicle pose estimation.
• Develop and fine-tune differentiable pose estimation solvers and neural matching techniques to improve or supplant conventional association and filtering methods.
• Design robust camera-based SLAM and Visual-Inertial Odometry (VIO) solutions tailored to urban and structured environments.
• Integrate localization capabilities seamlessly with navigation, planning, and vehicle control frameworks.
• Collaborate across multidisciplinary teams to embed localization software within integrated autonomous systems.
• Conduct research and implement state-of-the-art methods in visual localization, mapping, state estimation, and machine learning technologies.
• Contribute actively to enhancing software architecture, boosting performance, scalability, and reliability.

Qualifications & Skills

• Comprehensive experience with HD map-based localization using standards such as Lanelet2 and OpenDRIVE or similar formats.
• Expertise in differentiable optimization, neural pose estimation, and familiarity with machine learning libraries like PyTorch, PyPose, Theseus, or equivalents.
• Strong proficiency in non-linear optimization and state estimation via frameworks like Ceres, g2o, or GTSAM.
• Deep understanding of Bayesian filtering strategies and autonomous navigation principles.
• Advanced knowledge in coordinate transformations, Lie groups/algebras (SO3, SE3), and geometric reasoning in 2D/3D spaces.
• Proficient in modern C++ (C++17/C++20) and Python programming.
• Extensive experience with ROS 2 and developing robotics software.
• Track record of crafting high-performance production software on Linux platforms.

Preferred Qualifications

• Experience with learned Bird’s Eye View (BEV) representations and probabilistic map alignment.
• Familiarity with autonomous driving software ecosystems and modular autonomy system architecture.
• Knowledge of geometric deep learning and spatial data association techniques.
• Applied machine learning expertise in visual odometry, scene understanding, or perception tasks.
• Exposure to large-scale robotics or autonomous vehicle deployments.

Education

Master’s or PhD degree in Robotics, Computer Science, Electrical Engineering, Computer Engineering, or closely related disciplines.