About Universe Energy
We make grid batteries from used EVs with robots to electrify the world and reverse mining.

Our mission is to replace mining with reuse as the largest source of the next billion batteries. The problem is that batteries are expensive to reuse today because of non-standardized testing, expensive shipping, and dangerous disassembly by hand. We collect and sort old batteries, test how good they still are, and take them apart. We do this for all types of EV batteries using ML-driven analytics & intelligent robotics. Then we turn them into modular, directly accessible, and low-cost grid storage systems. If we can’t do this, we prepare them for recycling to turn them into raw materials to make new cells. Our vision is to build local factories around the world to become the largest manufacturer of used batteries and their raw materials to realize a truly clean energy revolution.

The Bonobo Robot
To achieve this mission, we build cognitive robots called Bonobo that automatically diagnose, discharge and disassemble EV batteries using ML-based analytics and intelligent robotics. The first-generation robotic system will automatically assess the battery’s state of health, perform safe discharging, and remove covers from arbitrary battery packs (500kg). It then disassembles these batteries from the pack level (500 kg) down to the module- level (25 kg). Bonobo can take batteries apart 4x faster and safer than a human at 6x the throughput, leading to 50% lower unit economics.

Job objective
You will conceptualize, architect, engineer and deploy algorithms that allow the robot to see and recognize the configuration of EV battery packs. The perception system then instructs the robot how and what to see and identify parts like screws, welding seams, cables, and modules. Then it instructs Bonobo robot how to take these apart. Ultimately, you will validate the software with what the cameras on the Bonobo see.

How you will contribute

  • Develop production-level & robust computer vision modules for classification, counting, tracking, 3D reconstruction, camera calibration, and segmentation.
  • Research and implement machine perception & visual understanding of battery systems to enable counting, detection, localization, and labeling
  • Build perception software that integrates computer vision, sensor fusion, decision-making functions, and structures data-set generation.
  • Develop and implement classical and learning-based computer vision on real-time platforms.
  • Perform sensor selection for the camera perception system like RGB, infrared, and laser scan. Develop sensor-fusion and decision making algorithms.
  • Generate datasets for algorithm training from both the real world & synthetic. Configure infrastructure for machine perception capabilities.

The skills & experience that you bring

  • At least a B.Sc. in Computer Science, Applied Mathematics,Machine Learning, or a similar field.
  • Academic background in Applied Mathematics, Machine Learning, classical Computer vision, Image recognition, and Perception systems.
  • 3+ yrs experience in developing software with strong skills in C/C++, Python, and Matlab-Simulink and have developed software from architecture to production-level code in software, ML, and perception environments.
  • 3+ yrs experience in developing ML tools in Torch/TensorFlow built and Classical computer vision algorithms in C++ and OpenCV.
  • 3+ Experience in generating, filtering and augmenting large image datasets for computer vision.
  • 1-3 yrs Experience developing, training, and testing deep-learning-based algorithms for detection, counting, classification, segmentation, and tracking.
  • 1-3 yrs hands-on experience with optical, image sensor, or camera calibration, and their associated computer vision principles to process this data.

How to hit a homerun

  • A track record of relevant academic publications, patents, and/or open-source software in machine learning and/or computer vision.
  • Hands-on experience processing rich sensor data from LIDAR, RADAR, and camera from autononous driving environments.
  • Experience in 3D graphics, focusing on 3D geometry manipulation (Vis-Rep, B-rep geometry representations) & Game engine experience in Unity3D (C#) or Unreal Engine (C++).
  • Hands-on experience with building autonomous and/or robotic systems is a plus.

Reach out to careers@universeenergy.ai for questions, comments and/or feedback before applying.

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