Waymo is looking to improve its autonomous driving technology by optimizing the Perception team's system for learning spatial-temporal representation and semantic meanings of the surrounding environment.
Requirements
Experience with Python
Experience with ML frameworks like PyTorch or JAX
Experience with C++
Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI
Responsibilities
Optimize FLOPs utilization in model training and model inference through model architecture/ hardware co-development, optimize for a naturally sparse representation (most spatial-temporal information in self-driving is sparse).
Optimize model inference for different onboard and offboard (simulation) platforms.
Analyze and optimize real-time inference of complex model architectures with many model components as well as on the critical path within an onboard system.
Other
Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
3+ years experience in Machine Learning and/or Computer Vision
MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline
