Tasks:
- * Build production data-loop and model-iteration pipelines
- * Develop autonomous driving perception algorithms
- * Develop world models and generative simulation models
- * Model and optimize urban, highway, and parking scenarios
- * Research end-to-end driving foundation models
- * Track and evaluate emerging AI and autonomous driving methods
Perks/Benefits:
Skills/Tech stack required:
[3D Gaussian] [3D Gaussian Splatting] [Autonomous Driving] [Autonomous driving perception] [BEV perception] [C++] [CUDA optimization] [Deep learning] [Distributed Training] [Driving simulation] [End to End] [End-to-End Autonomous Driving] [Gaussian Splatting] [Generative AI] [Image sensor] [Image Sensor Simulation] [Linux] [Motion Prediction] [Multimodal Generation] [Nerf] [Neural Rendering] [Occupancy prediction] [Python] [PyTorch] [Sensor Simulation] [Sim-to-Real] [SLAM] [TensorFlow] [World Models]
Educational requirements:
N/A
Role(s):
[Algorithm Engineer] [Autonomous Driving Algorithm Engineer] [Deep Learning Engineer] [Engineer] [Learning Engineer]