Motion Planning & Control Engineer – Self-Driving

We areseekinga highly skilledExperts,Seniors, Engineersto join our self-driving team. In this role, you will design, develop, and deploy advanced algorithms that enable autonomous vehicles to accurately sense, interpret, and interact with the world around them. You will work oncutting-edgechallenges in 3Dobject and occupancydetection, tracking, sensor fusion, scene understanding, and foundation models for self-driving, with direct impact on the safety and performance of our autonomous systems.This is an opportunity to contribute at the intersection of deep learning, computer vision, robotics, and system engineering, while collaborating with a world-class team of researchers and engineers.

• Design, develop, and optimize motion planning algorithms that handle complex, interactive traffic scenarios
  

• Formulate and implement trajectory generation methods that balance safety, comfort, and efficiency under real-world driving conditions
  

• Research and applystate-of-the-artplanning methods, including optimization-based approaches, probabilistic decision-making, reinforcement learning, and imitation learning
  

• Integrateperception, prediction, and mapping outputs into planning pipelines for robust decision-making
  

• Ensure real-time performance of planning algorithms on automotive-grade embedded hardware
  

• Contribute to the development of closed-loop validation pipelines, including simulation, software-in-the-loop, hardware-in-the-loop, and on-road vehicle testing
  

• Collaborate with multidisciplinary teams (perception,prediction,map generation,controls, systems) to integrate planning algorithms into the self-driving autonomy stack
  

• Stay current with advances in motion planning, decision-making, and learning-based approaches for autonomous driving
  

• Driveengineering excellence by writing clean, efficient, and well-tested code
  

• Strong background in motion planning, trajectory optimization, and decision-making methods (e.g., A*, optimization-based planning, graph searchetc.)
  

• Experience with reinforcement learning, imitation learning, or deep learning approaches for planning and control
  

• Proficiencyin Python and C++, with familiarity in ML frameworks such asPyTorchor TensorFlow
  

• Solid understanding of vehicle dynamics, kinematics, and control theory
  

• Hands-on experience with real-time systems, performance optimization, and deployment on embedded automotive hardware
  

• Skilled in simulation-based development and validation using tools such as CARLAor MATLAB/Simulink
  

• Strong mathematical foundation in optimization, linear algebra, probability, and statistics
  

• Excellent problem-solving skills and ability to work in fast-paced, collaborative environments
  

• Prior experience in self-driving or ADAS development and familiarity with functional safety standards (ISO 26262, SOTIF)