To help facilitate administration of relocation benefits if you are selected, please apply using the permanent address you would move from.
Work Arrangement:
Hybrid: This internship is categorized as hybrid. The selected intern is expected to report to the office up to three times per week or as determined by the team.
Offboard perception: Unlike onboard perception, which must run in real time on the AV, offboard perception can leverage larger models, greater compute, and acausal processing to achieve much higher accuracy. These high-accuracy detections support multiple consumers across the organization—for example, powering simulation and generating automated labels used to train onboard models.
As a Machine Learning Engineering Intern, you will work alongside a world-class team of engineers and researchers on impactful AI/ML projects in robotics and advanced manufacturing. You’ll gain hands-on experience contributing to the design, prototyping, and potential deployment of AI systems in real-world industrial settings. This is an excellent opportunity to explore applied research and development while learning from top experts in the field.
-
Help build and test components of end-to-end deep learning pipelines that process multimodal sensor data (e.g., cameras, lidars, radars).
-
Currently enrolled in a PhD program in Computer Science, Machine Learning, Robotics, or a related STEM field.
Preferred Qualifications:
-
Hands-on experience with one or more machine learning frameworks (e.g., PyTorch, TensorFlow, JAX, or Keras).
What you’ll get from us (Benefits):
