Post Master
NIST is investigating the performance of commercial and custom AI systems (hardware and software) for printed circuit board (PCB) inspection and manufacturing defect detection. The work will focus on conducting experiments, acquiring and analyzing data to understand these systems' performance, and generating data to train AI systems.
Machine Vision and AI/ML Engineer - PCB
● Education:
- Engineering majors with a Ph.D or master’s degree (Ex: Computer Science,
Computer Engineering, Robotics, Electrical Engineering, and/or Mechanical
Engineering)
● PCB design and hardware:
- Experience with PCB layout and design software such as KiCad, DipTrace
- Experience with developing and inspecting PCBs
● AI/ML and computer vision:
- Experience using Python, PyTorch, and Tensorflow for developing AI/ML
pipelines. - Experience with OpenCV, MVTec HALCON, or Matlab Computer Vision Toolbox.
- Basic understanding of imaging sensors such as RGB and RGB-D cameras
- Experience with computer vision algorithms to perform object detection, data
augmentation, and 2D/3D pose estimation - Point cloud data processing, 2D and 3D imaging
● Experience with physics engines such as Unity, Unreal Engine and MuJoCo.
● Experience developing on both Windows and Linux platforms.
● Experience with CAD software such as SolidWorks and OnShape
Key responsibilities will include but are not limited to:
● Develop AI/ML based image processing pipelines using Python/Pytorch and other
relevant software modules in collaboration with other NIST researchers.
● Develop test rigs to acquire 2D and 3D images of PCBs and defective parts.
● Research the effects of various physical properties of an object and sensor settings on
the AI metrics.
● Write reports and develop weekly presentations to discuss the progress of the project.
● Perform a literature review and market research of relevant algorithms, hardware and
software.