Perception Intern (Fall 2026)

You must have completed the second year of your undergraduate studies.

A proven history of quality ML research, reflected by publications in conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, CoRL, RSS, etc.

Specific expertise in areas such as multi view depth estimation, semantic segmentation, generative modeling, etc.

Proficiency with deep learning frameworks like PyTorch, JAX, or TensorFlow.

Experience writing code in a production environment, e.g.

You'll dive into ML model experimentation, evaluation and integration -  pushing the boundaries of our current offboard perception system.

Join us, and be at the frontier of shaping the future of autonomous deliveries.

Leverage heterogeneous sources of data (real-world, simulation and internet-scale data) to train machine learning models.

Ship production code to train, validate and integrate models into the perception system.

The Droid Perception team owns both onboard and offboard (cloud-side) perception systems that inform, validate, and augment our onboard autonomy. From generating rich 3D and semantic priors from aerial survey data to learning customer preferences and terrain features at scale, your work will help define how we prepare Zipline aircraft to perform mission-critical deliveries in complex, real-world environments.