Responsibilities
- Developing and optimizing deep learning models for end-to-end driving.
- Designing and working with spatio-temporal neural networks.
- Building scalable pipelines for data processing and model training.
- Training models on large-scale datasets and integrating them into production systems.
- Experimenting with architectures such as transformers and recurrent neural networks.
- Collaborating with other specialist teams to deploy models in real-world scenarios.
Requirements
- Deep knowledge of spatio-temporal neural networks.
- A strong background in deep learning, software development, and data engineering.
- Strong proficiency in Python.
- Experience with deep learning frameworks such as PyTorch or TensorFlow.
- Strong proficiency in C++.
- A solid understanding of statistics and geometry.
- Strong analytical and problem-solving skills, combined with the ability to collaborate effectively with others.
Desired Skills
- Transformers.
- RNNs.
- Multi-head attention.
- Perception systems, including computer vision, lidar, and radar.
- Tracking.
- Sensor fusion.