Computer Vision R&D Engineer

190506
  • $120,000.00 to $200,000.00
  • Duluth United States
Computer Vision R&D Engineer (3D Imaging / Machine Learning)
Location: Atlanta, GA (or flexible depending on your preference)
About the Opportunity
We are partnering with an innovative engineering organization developing next-generation 3D imaging and inspection systems used across advanced manufacturing, medical technology, and robotics applications.
This is a highly collaborative R&D environment where computer vision engineers work alongside experts in software, robotics, optics, electronics, and physics to build cutting-edge solutions powered by machine learning and computational imaging.

What You’ll Do
  • Design and develop advanced computer vision algorithms for:
    • 3D reconstruction (e.g., structured light, multi-view geometry)
    • 2D/3D imaging and camera calibration
    • Object detection, segmentation, denoising, and metrology
  • Research and implement machine learning / deep learning models for complex vision challenges
  • Build and deploy end-to-end vision systems using C++ and Python
  • Optimize algorithms for performance and scalability, including GPU/CUDA acceleration
  • Develop solutions for inspection systems, medical devices, and robotics platforms
  • Collaborate cross-functionally with global engineering teams
  • Contribute to a highly innovative culture with regular idea-sharing and technical exploration

What They’re Looking For
  • MS required (PhD preferred) in Computer Science, Computer Engineering, Robotics, or related field
  • Strong background in computer vision and/or machine learning
  • Hands-on experience developing and optimizing algorithms in C++ and/or Python
  • Experience with GPU/CUDA or parallel processing
  • Familiarity with vision/ML frameworks such as:
    • OpenCV, PyTorch, TensorFlow, Caffe, etc.
Experience in at least one of the following areas:
  • 3D vision (structured light, stereo, multi-view geometry)
  • Image processing and vision algorithm optimization
  • Deep learning (CNNs) for vision applications
  • High-performance computing and algorithm optimization
  • Embedded or real-time vision systems
Kristen Tiftickjian Division Manager

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