6 months ago
Berlin, GermanyMid Level
Responsibilities
- Design real-time state estimation pipelines for vehicle velocity, angular velocity, and position.
- Fuse LiDAR, IMU, GNSS, radar, and wheel odometry data using probabilistic estimation frameworks.
- Implement and maintain filter-based and optimization-based estimators, including EKF, UKF, and factor-graph methods.
- Integrate estimation modules with robotics stacks and validate performance through simulation, log analysis, and real-world testing.
- Diagnose estimation failures and reason about system-level robotics behavior.
Requirements
- Hands-on experience implementing robotics state estimation algorithms such as Kalman filters, optimization-based estimators, or particle filters.
- Experience estimating vehicle motion by fusing data from multiple robotic sensors.
- Strong programming skills in C++ and/or Python, ideally in ROS or ROS2 environments.
- Strong analytical and debugging skills.
- Experience in autonomous vehicles, robotics, or off-road systems is preferred.
- Knowledge of SLAM, localization, or factor-graph frameworks such as GTSAM or Ceres is preferred.
- Understanding of vehicle dynamics and control integration is preferred.
- Experience validating robotics systems through simulation and field testing is preferred.
Benefits
- Attractive compensation package and stock options.
- Assistance with relocation to Berlin.
- Beverages on-site and regular social events.
- Opportunity to work with top-tier researchers, engineers, and thought leaders.
- Opportunity to shape physical AI and robotics for heavy off-highway machinery.
- Career paths toward technical specialization or technical team leadership.
