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Motion Planning Engineer (m/f/d)

CompraTica Empleos

EMP:Technology
Berlin
Tiempo Completo
Remoto
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Descripción

Driving the transition to autonomous mobility: Our mission is to spearhead the deployment of Level 4 autonomous systems in Germany and beyond.

By combining cutting-edge AI with the expertise of our multidisciplinary team, we are set to introduce the first certifiable solution of its kind to European roads.

Since 2017, we have remained dedicated to one goal: shaping a future that is already in motion.

Tasks Design and implement motion planning algorithms that generate safe and efficient vehicle trajectories under diverse driving conditions Optimize planned trajectories for safety, comfort, and efficiency, balancing competing constraints in real time Validate motion planning behavior in simulation and on real-world test data, identifying and resolving edge cases Work closely with perception and software integration teams to ensure motion planning outputs integrate reliably into the overall driving stack Ensure motion planning algorithms meet defined performance benchmarks and safety.

Requisitos

for autonomous operation Requirements A completed degree in computer science, robotics, engineering, applied mathematics, or a comparable field - or equivalent vocational training/apprenticeship in a relevant technical discipline

Hands-on experience counts at least as much as the formal qualification 3+ years of experience in motion planning, robotics, or autonomous vehicle software Proven experience developing motion planning/trajectory generation algorithms for robotics or autonomous vehicles, with a solid background in optimization techniques (e.

model predictive control, sampling-based planners) Strong C++ and/or Python.

Habilidades

, with experience in motion planning frameworks/libraries (e.g

OMPL, MoveIt) and optimization solvers for trajectory optimization/MPC (e.

CasADi, OSQP, IPOPT) Experience with ROS/ROS2 and simulation environments (e.

CARLA, Gazebo), plus a solid grounding in control theory and state estimation (e.

Kalman filters), linear algebra, and numer.

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