Solve the autonomous driving problem by establishing a state-of-art ML infrastructure for training very large foundation models and accelerating model training/inference.
Requirements
- Good knowledge of PyTorch
- Knowledge of model training framework (e.g. PyTorch Lightning)
- Knowledge of transformer architecture and ways to accelerate the training and inference of transformer models
- Experience of using pytorch ddp for distributed training of models
- Experience in training large scale vision or language models
- Previous experience in the autonomous driving industry
- Knowledge of distributed training
Responsibilities
- Design, train, and deploy large deep learning models that can leverage the vast amount of labeled and unlabeled data from a fleet of million vehicles.
Other
- Master in CS/CE/EE, or equivalent, with 3 + years of industry experience
- PhD in CS/CE/EE, or equivalent, with 1 + years of industry experience
- Strong publications records in top academic conferences or journals, e.g. CVPR, NeurIPS, ICML, ICCV, ECCV, ICLR
- Being efficiently in solving complex problems collaboratively on larger teams
