Role SummaryAs 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.
Responsibilities- 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
Qualifications- 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
Pay DisclosureSalary Range for California Based Applicants: $228,000.00 - $285,000.00 (actual compensation will be determined based on experience, location, and other factors permitted by law).
Benefits Summary: Rivian provides robust medical/Rx, dental and vision insurance packages for full-time employees, their spouse or domestic partner, and children up to age 26. Coverage is effective on the first day of employment
Please note that we are currently not accepting applications from third party application services. 
