about 4 hours ago
Base Salary
$242k - $290k/yr
Responsibilities
- Design and implement multi-modal sensor fusion architectures for 3D occupancy and segmentation.
- Develop vision-first fusion strategies to enhance geometric understanding.
- Engineer temporal processing modules for stable and consistent predictions.
- Optimize model architectures for real-time on-vehicle inference.
- Collaborate with downstream teams to refine geometric outputs for navigation.
Requirements
- MS or PhD in Computer Science, Robotics, Machine Learning, or related field with 6+ years of industry experience.
- Deep expertise in 3D Computer Vision and Deep Learning, particularly with voxel-based or BEV architectures.
- Strong proficiency in Python and deep learning frameworks like PyTorch, with some C++ experience.
- Experience with multi-sensor fusion and handling temporal data sequences.
- Familiarity with occupancy networks and implicit representations.