As a Staff Software Engineer, ML training and inference infrastructure, you will be a member of the Perception team at Rivian, which develops advanced machine learning algorithms that directly impact safety critical self-driving features of our category defining vehicles.

We are looking for candidates with deep knowledge and strong enthusiasm towards establishing a state-of-art ML infrastructure for training and inference of large autonomous driving models; and optimizing the training and inference performance. 

• Optimize the performance of Deep Learning training workload on NVIDIA GPU systems on a large scale
• Optimize the latency of model inference and model pre- and post-processing on onboard systems
• Design, train, and deploy large deep learning models that can leverage the vast amount of labeled and unlabeled data

• PhD in CS/CE/EE, or equivalent, in industry experience
• Deep knowledge of PyTorch
• Knowledge of model training framework (e.g. PyTorch Lightning, ray, etc.)
• In-depth knowledge of transformer architecture and ways to accelerate the training and inference of transformer models
• Experience of performing large scale distributed training of models
• A track record of profiling models and doing detective work to improve model training and inference speed

Preferred Skill Requirements:

• Experience with CUDA or Triton language for writing custom ops
• Knowledge of Nvidia TensorRT
• Knowledge of NCCL
• Experience with edge computing systems
• A track record of efficiently solving complex problems collaboratively on larger teams