Sr. Staff Engineer

Develop trajectory optimization algorithms, including iLQR- and MPC-based approaches, for low-speed autonomous driving scenarios. Design constraint-aware optimization methods and improve local planners to generate control-friendly trajectories. Refactor and scale planning-stack architecture for maintainability, extensibility, and operation across scenarios and vehicle platforms. Optimize CPU usage and investigate parallel and GPU acceleration opportunities. Debug curvature discontinuities, velocity and trajectory mismatches, and edge-case steering behavior using simulation, vehicle logs, multi-scenario testing, and benchmarking. Prototype and evaluate learned models, barrier functions, and ML-based planning approaches for production viability. Drive technical discussions, document algorithm insights, support knowledge transfer, and track work in Jira. Responsibilities Develop trajectory optimization algorithms, including iLQR- and MPC-based approaches, for low-speed autonomous driving scenarios. Design constraint-aware optimization methods and improve local planners to generate control-friendly trajectories. Refactor and scale planning-stack architecture for maintainability, extensibility, and operation across scenarios and vehicle platforms. Optimize CPU usage and investigate parallel and GPU acceleration opportunities. Debug curvature discontinuities, velocity and trajectory mismatches, and edge-case steering behavior using simulation, vehicle logs, multi-scenario testing, and benchmarking. Prototype and evaluate learned models, barrier functions, and ML-based planning approaches for production viability. Drive technical discussions, document algorithm insights, support knowledge transfer, and track work in Jira. Requirements M.S. or Ph.D. in Robotics, Control, Electrical Engineering, or a related field. 10+ years of software development experience in autonomous driving, ADAS, or robotics, focused on large-scale data and real-time systems. Strong C/C++ programming skills and understanding of software engineering design principles and best practices. Experience delivering ADAS or autonomous-driving features through requirements analysis, architecture and design, implementation, unit testing, feature tuning, SIL/HIL validation, and in-vehicle deployment. Hands-on experience integrating software on embedded platforms such as NVIDIA Xavier/Orin and Infineon Aurix. Ability to build reliable production-grade systems, large-scale architectures, evaluation pipelines, and performance-optimized models. Leadership experience. Preferred qualifications include ML-based planning, GPU or parallel computing for planning, and production deployment in real vehicles. Benefits Medical, dental, and vision insurance; life and disability coverage; paid time off; paid holidays; paid sick leave; and a 401(k) retirement plan. Eligible employees may participate in Lucid's equity program and/or discretionary annual cash incentive program. The position is based in Newark, California and requires onsite work five days per week. #J-18808-Ljbffr Lucid Motors