Create foundation scale data sets and training recipes, develop methods and recipes for human and machine labeling of foundation scale data sets.
Create methods and recipes for continuous data intake, selection and incremental updates of large models, develop methods for data mining and recipes for automated data collection/model update flywheels.
Develop methods and recipes for evaluating real-world performance of models, and detecting regressions in model updates.
Develop and maintain ground-truth free performance metrics.
You have:
Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
3+ years experience in Machine Learning and/or Computer Vision
Experience with Python
Experience with ML frameworks like PyTorch or JAX
We prefer:
MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline
Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI
