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Join the Automotus team!

Computer Vision Intern


Automotus is a fast-growing technology startup working to make city streets safer, more sustainable, and more efficient––starting at the curb.



We use computer vision (CV) deployed at the edge to build the first fully-automated platform for cities to understand and manage curbside activity, which means everything from freight, ride-hailing, and food delivery services, to passenger vehicles and buses.

The success of Automotus depends on our ability to deliver insights and operational automations to our clients from the data we generate using our CV processors at the edge. On our computer vision team, you will be a key contributor to the technology at the foundation of everything we do. You will have an opportunity to take part in the R&D of a world-class CV product at all stages in the pipeline: from data collection and labeling strategies, to experimenting with state-of-the-art CNN architectures, to assessing and improving model performance.


An ideal candidate is someone with a strong foundation in Computer Vision and a keen interest in applying that knowledge towards making city streets safer and more efficient for everyone.  


  • Help build, automate, and customize deep learning training and inference environments

  • Implement automations to improve the velocity of training data collection and annotation

  • Research and Experiment with state-of-art CNN architectures for effective object detection

  • Research and Develop methods for automatically assessing and tuning vision pipeline hyperparameters

  • Assist in the overall development and testing of our CV pipeline


  • Well-developed understanding of CNNs for object classification and detection tasks

  • Experience training and deploying object classification/detection models on a cloud platform (e.g. AWS, GCP, Azure).

  • Experience working with a scripting language (Python or Javascript preferred)

  • Experience working with C/C++

  • Experience developing software using UNIX-based operating systems

  • Experience working with a VCS (Git preferred)

  • Experience using at least one deep learning SDK (eg. Tensorflow, Caffe/PyTorch) for object detection/classification tasks


  • Experience writing, testing, and deploying production-level code

  • Established knowledge of GPU hardware

  • Strong bash scripting skills

  • Experience developing applications using Gstreamer 

  • Experience with software performance profiling and optimization


  • Competitive Pay

  • Opportunity to learn and experiment with state-of-the-art computer vision technologies

  • Flexible hours

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