Define and drive the technical vision and architecture for trajectory generation systems used in autonomous driving
Lead the development of ML-based trajectory generation models capable of handling complex and dynamic driving environments
Architect scalable training pipelines using large-scale driving datasets and simulation environments
Guide the integration of trajectory generation models into real-time onboard systems with strict latency and safety requirements
Influence the design of next-generation embodied AI architectures for driving
Mentor senior engineers and help develop the next generation of technical leaders
Raise the bar for engineering excellence, modeling rigor, and production-quality systems
Foster a culture of innovation, ownership, and collaborative problem solving
Lead complex technical initiatives spanning multiple teams across the autonomous driving stack
Collaborate closely with teams working on data, perception, simulation, safety validation, onboard systems
Define roadmaps and priorities aligned with product milestones and safety goals
Drive solutions from research prototypes through production deployment
Requirements
MS or PhD in Computer Science, Robotics, Machine Learning, or related field
Experience leading technical teams delivering production ML systems
Deep expertise in one or more areas: robotics planning and control, imitation learning or reinforcement learning, generative models, large-scale machine learning systems
Strong software engineering skills (Python, C++, or similar)
Experience deploying ML models into real-world or safety-critical environments
Demonstrated ability to define architecture and drive large technical initiatives across teams