Algorithm Development: Support the development of route optimization andmotion planning algorithms (graph search, sampling, or optimization-basedmethods) based on designs provided by the research team.
Software Development: Writeclean, maintainable, and efficient C++ code to integrate planning modules intothe core autonomy stack.
Simulation & Validation:Own the end-to-end testing of planning stacks in simulation. You will beresponsible for identifying corner cases, debugging planningfailures, and ensuring trajectory smoothness.
Performance Optimization:Assist in profiling and optimizing existing algorithms to ensure they meetreal-time constraints and operate efficiently on embedded hardware.
Field Testing & Analysis:Participate in real-world vehicle testing. Analyze logs and telemetry data totroubleshoot behavior inconsistencies and improve system reliability.
Cross-Functional Support:Collaborate with the Perception and Control teams to ensure seamless data flowand coordinate transform accuracy across the stack.
Required experience
Educational Background: Master's or Bachelor's degree in ComputerScience, Robotics, Engineering, or a related field. A strong academicfoundation in path planning or autonomous systems is required.
Programming Proficiency: Solid proficiency in Modern C++. Familiaritywith Python for scripting and data analysis is a plus.
Robotics Fundamentals: Good understanding of standard planningalgorithms (e.g., A., RRT., Frenet frames, or Lattice planners) and basickinematics.
Hands-on Tools: Experience with Linux (Ubuntu) and ROS/ROS2 isessential.
Growth Mindset: A proactive tinkerer attitude with theability to learn complex new frameworks quickly and a desire to solve'hard robotics problems.
