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The Summer Intern session is a 12-week, full-time (40 hours Monday-Friday) program while the Co-op cohorts typically run 16-weeks in the Spring and Fall. In both programs, students are paid a competitive hourly rate. Symbotic’s Machine Learning team is an accomplished group of engineers who are working on sophisticated algorithms in areas such as routing, perception, and computer vision. Perception and Computer Vision interns will evaluate and propose new projects for replacing legacy tools with vision-based algorithms. These interns will scope projects from literature review, to dataset design and aggregation, training pipeline development, all the way through production deployment. Practical projects include vision-based collision avoidance.
Job Responsibility:
Research and experiment with traditional computer vision methods and deep learning methods for object detection, classification, segmentation, pose estimation, anomaly detection on images or videos
Evaluate and benchmark computer vision methods on production data
Deploy software to production on robot hardware
Design data pre and post processing methods
Document designs, code, experiments, evaluations
Identify high-impact scenarios where AI Planning and machine learning can be applied to optimize the Symbotic robotics software
Adapt state-of-the-art approaches or develop high-performance algorithms to solve real-world multi-robot problems
Conduct simulations and experiments to validate the performance of the multi-robot algorithms
Present results in verbal and written communications internally, and in top-tier academic venues
Requirements:
Currently pursuing PhD or Masters degree in Computer Science or other related discipline required
Strong programming skills in Python and/or C++ (Python is preferred)
Experience with ML frameworks such as PyTorch and/or Tensorflow (PyTorch is preferred)
Experience with image processing such as OpenCV
Enjoys learning new technologies, skills, and techniques as well as teaching them to others
Nice to have:
Publications at high-impact conferences/journals (e.g., CoRL, ICLR, NeurIPS, ICML, ICLR, RSS, ICRA, IROS, RAL, AAAI, ICAPS, IJCAI, JAIR, etc.) on some of the aforementioned topics
Experience with RGB cameras (pinhole camera model, calibrations, projections)
Experience with 3D sensors and point cloud processing such as PCL
Experience with embedded computing such as Nvidia Jetson
Experience with code revision control (git)
Experience with containerization (docker)
Experience with using the command line (bash)
Experience with transformation between coordinate systems (homogeneous transformations, Euler angles, quaternions)
Experience with cloud-hosted environments (AWS, GCP, Azure)