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Computer Vision Research Scientist



Software Engineering
Sterling, VA, USA
Posted on Monday, March 18, 2024

Company Overview: Dedrone is the world’s most trusted smart airspace security company. Hundreds of commercial, government and military customers around the world rely on Dedrone’s comprehensive, command and control (C2) solution to protect against the persistent and escalating threat from drones while enabling “good” drones to fly. By leveraging AI/ML, Dedrone is the only solution that provides continuous, autonomous interrogation and verification of drones that enables both multi-sensor and multi-mitigation options onto a single fused "pane-of-glass". Whether on-premise / air-gapped or in the cloud, Dedrone customers can easily detect, track, identify, analyze, and mitigate drone threats.

Dedrone is looking for a team member to research, develop, and train deep-learning computer vision models and advance object-tracking algorithms. Dedrone's global sensor network, data science team, and computing cluster offer an ideal environment for research and development. We seek someone experienced in visual object tracking and modifying neural network training recipes and architectures to solve complex computer vision problems.

You will…

  • Research, develop, and train deep-learning computer vision models and advance object-tracking algorithms
  • Work closely with cross-functional teams to identify opportunities to leverage computer vision technology to solve complex business problems.
  • Develop and maintain relationships with external partners, vendors, and research organizations.
  • Develop, implement, and optimize computer vision algorithms for processing and analyzing medical imaging data,

You have…

  • Degree in Computer Science, Mathematics, Physics, Electrical Engineering, or a related field.
  • Proficient in PyTorch
  • Skilled in ML experiment creation and analysis of results
  • Good understanding of target tracking concepts such as data association and state estimation.
  • Deep understanding of deep learning object detection models. Able to clearly explain the difference between YOLOV4 and Faster R-CNN.
  • Experience working with academic and industry partners in a collaborative and international environment
  • Proactive problem-solving skills. Willingness to constantly learn and ability to spot and resolve problems in a team setting.

At Dedrone, we believe that great ideas come from anywhere. We support a collaborative environment and value open participation from individuals with different ideas, experiences, and perspectives. We believe having a diverse team makes Dedrone a more interesting and innovative place to work, and we strive to make Dedrone a welcoming and inclusive place for all.