Luma AI·Machine Learning Engineer·Technical Phone Screen
- Walk through how you'd implement around 10 image augmentations for grayscale digit images in a denoising training pipeline, including things like random resize, crop, rotation, flips, brightness/contrast jitter, Gaussian noise, elastic distortion, and cutout. Cover in-place operations, before/after visualizations, autograd safety, and how you'd seed the pipeline for reproducibility.
“This was a lot to unpack in one question.”