Aurora is looking to solve the problem of training and validating sensing models for autonomous vehicles using synthetic data
Requirements
- Excellent software engineering skills in Python
- Experience in Deep Learning (2+ years preferred)
- Experience in Computer Vision or generative Computer Graphics
- Experience with Pytorch/Tensorflow/Jax or similar frameworks
- Experience with synthetic training data
- Previous experience with generative ML models, e.g. diffusion models
Responsibilities
- Work on research, development, and deployment of state-of-the-art methods in computer graphics/vision and machine learning
- Train sensing ML models on synthetic training data
- Collaborate across various cross-team projects, providing ample opportunities for growth and impact on the Aurora Driver
- Help unlock new sensing model capabilities using synthetic training data
- Develop generative AI data generation pipelines
- Surface high-impact findings to relevant Engineering leadership, keeping feedback loop going to influence Aurora’s synthetic data and ML strategy
Other
- Bachelor’s degree in Computer Science or a related field
- Strong critical thinking, collaboration, and communication skills
- Master’s or PhD in Computer Science
- Top-tier publications in related fields (e.g., CVPR, ECCV, ICCV, IJCV, ICML, NeurIPS, JMLR, PAMI, SIGGRAPH, TOG)
- Commitment to inclusion and diversity
