Develops high-performance C++ motion planning algorithms for autonomous vehicles, including trajectory generation, pathfinding, and real-time optimization. Collaborates with perception, prediction, and control teams; requires strong algorithms knowledge and production code experience.
Salary not listed
On-siteEmbedded Engineering
About the role
What You'll Do
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
What You'll Need
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
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
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