Our team develops the core software and data processing systems that power motion planning and decision-making in autonomous vehicles. We work at the intersection of machine learning, large-scale data infrastructure, and real-time vehicle control, collaborating across engineering, analytics, and product teams to deliver safe and intelligent driving capabilities., We are seeking a highly skilled C++ Software Engineer to join our core Motion Planning team. You will be at the forefront of developing the decision-making logic that enables our autonomous vehicles to navigate the complexities of the real world safely and efficiently. If you have a passion for solving hard algorithmic problems and writing high-performance code, this is the perfect opportunity for you., * Design, implement, and optimize cutting-edge motion planning algorithms in modern C++ (C++17/20)

• Develop robust solutions for trajectory generation, pathfinding, and behavioral decision-making in dynamic environments
• Analyze and debug system performance using simulation, log playback, and on-vehicle testing data
• Collaborate closely with engineers from Perception, Prediction, and Control teams to build a cohesive and reliable self-driving system
• Write clean, maintainable, and optimized production-quality code
• Profile and optimize algorithms to meet real-time performance constraints

• Exceptional proficiency in modern C++ and a deep understanding of object-oriented design principles
• Strong foundational knowledge of algorithms and data structures, particularly those relevant to robotics (e.g., graph search, computational geometry, optimization techniques)
• Experience with software development tools and practices, including Git, CI/CD, and code reviews

Nice to have

• Proven success in competitive programming contests such as Google Code Jam, Hash Code, Topcoder Open, ICPC, or similar events
• Professional or academic experience in robotics, specifically with motion planning
• Experience with performance-critical software development, including multi-threading and memory optimization
• Knowledge of machine learning techniques (e.g., reinforcement learning, imitation learning) applied to planning or decision-making problems
• Solid mathematical background, including linear algebra and probability theory
• Knowledge of GPU programming (e.g., CUDA, OpenCL) for accelerating algorithms

LS-MS1

Candidates are required to be authorized to work in the U.S. The employer is not offering relocation, sponsorship, and remote work options are not available.