You Have

• Proficient in modern C++ (11/14/17) and object-oriented programming
• Skilled in Python for rapid prototyping and testing
• Strong in debugging, profiling, and optimizing code
• Deep understanding of behavior planning algorithms such as state machines, behavior trees, and probabilistic planning
• Familiarity with path planning algorithms like A*, RRT, or optimization-based methods
• Master’s degree in Computer Science, Robotics, or a related field
• Minimum of 3 years of industry experience in autonomous driving, robotics, or a related field

We Prefer

• Knowledge of state machines, behavior trees, and decision-making under uncertainty
• Expertise in path planning algorithms such as A*, D*, and Rapidly-exploring Random Trees (RRT)
• Knowledge of machine learning techniques, especially in the context of behavior prediction and planning
• Experience with ROS / ROS2
• Implementing systems that can re-plan at high frequencies to adapt to dynamic changes in the environment
• Ensuring that behavior planning algorithms can execute with minimal latency for real-time navigation
• Proficiency in optimization techniques and probabilistic models for making informed planning decisions under uncertainty
• Master’s degree or PhD in Robotics, AI, Mathematics, or a related field with a focus on planning, optimization, or control theory is a plus