[소프트웨어/엔지니어] Sr. Path Planning Algorithm Engineer

A Sr. Path Planning Algorithm Engineer role is now open in a technology company. The selected candidate will lead path planning development using classical and learning-based methods for safe, efficient autonomous driving.

Responsibilities:

• Combine traditional search-based (A*, D*), sampling-based (RRT*, BIT*), and optimisation-based techniques with deep learning to improve path planning efficiency and quality
• Use deep learning-based heuristics, cost maps, and reinforcement learning-optimised sampling to accelerate search and enhance performance in complex environments
• Develop and own the behaviour planning layer, including state machines and decision-making logic for scenarios such as unprotected turns, merges, and obstacle avoidance
• Design and validate interfaces that integrate probabilistic outputs and uncertainty estimates from perception systems
• Utilise deep learning-based predictions of surrounding object behaviour to enable proactive and safe planning decisions
• Analyse real-world driving and simulation data to identify failure modes and drive continuous improvement of the planning stack
• Lead research and development of learning-based driving policies using imitation learning and reinforcement learning
• Design advanced reward functions that capture safety, efficiency, and passenger comfort beyond basic goal completion
• Develop hybrid planning architectures combining classical algorithms and learned policies for improved performance and reliability
• Use classical planners to bootstrap reinforcement learning models or provide safe fallback strategies
• Collaborate with vision and deep learning engineers to co-design policy network architectures for complex planning tasks
• Work with cross-functional teams to integrate multi-vision end-to-end algorithms into ADAS systems
• Support system integration across software, hardware, and machine learning components
• Participate in code reviews and knowledge-sharing initiatives to strengthen team collaboration

Requirements:

• Master's degree or above in Computer Science, Robotics, Engineering, or a related field
• More than 7 years of hands-on development experience in path planning, behaviour planning, or decision making for autonomous robots or self-driving cars
• Proven experience leading complex software systems from conception to deployment
• Expert-level proficiency in C++ and strong Python skills for prototyping and data analysis
• Deep theoretical understanding of robotics algorithms, including kinematics, dynamics, and probabilistic robotics

Preferred Requirements:

• Publication record in top-tier robotics or AI conferences such as ICRA, IROS, CoRL, RSS, NeurIPS, or CVPR
• Practical experience with one or more major E2E driving paradigms, such as imitation learning or reinforcement learning, in a robotics context
• Experience with optimisation-based trajectory generation and the use of numerical optimisation solvers
• Proficient in ROS/ROS2, middleware (DDS), and modern software development practices (CI/CD, Bazel, Git)

About the Company:

A leading provider of AI-based vision processing technology for autonomous vehicles and advanced driver assistance systems (ADAS). The company develops deep learning–powered software that enables vehicles to detect and recognise objects with high accuracy and efficiency.

Keywords:

엔지니어, 기술, 자동차, 로봇 공학

Job Ref: SRNCFK