Autonomous Vehicle Intern, Perception, Auto Labeling

Key Skills

AI Robotic systems, Computer Vision (CV), Effective communication skills, Machine learning techniques, NumPy, Python Programming, PyTorch

Job Description

Auto Labeling Team at Motional is looking for a highly motivated intern to join our team and help advance our Offline Perception system to the next level. The Auto Labeling team aims to develop algorithms to produce high-quality 4D annotations automatically at scale. This is critical for the future of autonomous driving as the Machine Learning models trained from large-scale annotated datasets have become one of the key solutions, whereas the cost and throughput of manual labeling cannot scale up with the amounts of data generated from our fleets’ daily operations. 

As part of the Auto Labeling team, you will be able to collaborate and learn from our world-class researchers and engineers, exploring several techniques to improve the object detection in our Offline Perception system. This is a unique opportunity for students to conduct cutting-edge research with access to our high-quality internal datasets as well as state-of-the-art computing infrastructure. The research outcome will have the potential to be published in the top-tier conferences as well as being deployed in our auto labeling pipeline. If you are a self-motivated computer science/engineering graduate student who is passionate about research and technology in autonomous driving, this is the place for you.

What you’ll be doing:

• Research, propose and implement novel ideas to improve the performance of Offline Perception system
• Explore to leverage the machine labeled data to boost the autonomous vehicle’s capability
• Write patents, reports and submit a research paper to top conference

What we’re looking for:

• PhD / Masters in Machine Learning, Robotics or similar fields
• Strong Python programming skills
• In-depth understanding of Machine Learning and Computer Vision tasks such as object detection, convolutional neural networks, etc.
• Proficiency in scientific computing and machine learning libraries, such as Numpy, PyTorch, etc
• Strong verbal and written communication skills
• Able to commit to a full internship for at least 6 months

Bonus points (not required):

• Proven track record of publications in relevant conferences (CVPR, ICML, NIPS, ICCV, etc.)
• Prior academic / industrial experience with Object Detection / Segmentation or other related tasks

Why you should join us:

• Accessibility to large scale internal datasets and computing infrastructure to conduct cutting-edge research
• Opportunity to get both academic publications as well as industrial impact
• Collaboration and guidance from world-class researchers and engineers from the industry