Image Processing SME Security Clearance

Overview

We are seeking a highly skilled Image Processing Subject Matter Expert (SME) to support the development of advanced imaging and signal processing solutions within a cutting‑edge FPGA engineering environment. The ideal candidate will possess deep expertise in scientific and computational imaging, image correction algorithms, machine vision, and automated image analysis.

This role will work closely with FPGA, software, hardware, and algorithm development teams to design and optimize image processing pipelines for high‑performance, mission‑critical applications. The successful candidate will contribute to the development of advanced imaging solutions involving microscopy, scientific sensors, electro‑optical systems, and other high‑resolution imaging platforms.

The position offers the opportunity to solve complex imaging challenges while supporting innovative technologies for government, research, and commercial applications.

• Analyze and develop image correction algorithms to compensate for optical aberrations, lensing defects, sensor non‑linearity, geometric distortions, illumination inconsistencies, and other imaging artifacts.
• Design, evaluate, and optimize advanced image processing pipelines for scientific and high‑resolution imaging systems.
• Develop algorithms for object detection, feature extraction, segmentation, classification, and pattern recognition within large image datasets.
• Create and optimize image stitching, registration, and mosaic generation techniques for microscopy and scientific imaging applications.
• Implement image preprocessing methods including noise reduction, deconvolution, contrast enhancement, normalization, filtering, and edge detection.
• Collaborate with FPGA engineers to transition computational imaging algorithms into hardware‑accelerated implementations.
• Evaluate algorithm performance, accuracy, throughput, and resource utilization for real‑time and near‑real‑time processing applications.
• Develop and validate machine learning and computer vision models for automated image analysis workflows.
• Support integration, testing, verification, and validation of imaging systems and processing pipelines.
• Work with multidisciplinary teams including FPGA developers, software engineers, optical engineers, data scientists, and system architects.
• Document technical designs, algorithm performance analyses, validation results, and implementation approaches.
• Provide technical leadership and subject matter expertise on imaging science, computational photography, and machine vision technologies.

• Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, Imaging Science, or a related technical discipline.
• 8+ years of experience developing advanced image processing, computer vision, or computational imaging solutions.
• Strong understanding of image formation, optics, sensor technologies, and imaging system performance characteristics.
• Demonstrated experience correcting scientific image data affected by aberrations, lens distortion, optical anomalies, non‑uniform illumination, and sensor artifacts.
• Expertise in object detection, feature extraction, image segmentation, and pattern recognition algorithms.
• Experience developing image registration, alignment, and stitching solutions for large‑scale image mosaics.
• Strong knowledge of image preprocessing techniques and enhancement methodologies.
• Experience handling large, high‑resolution image datasets while optimizing performance and computational efficiency.
• Proficiency in Python, C++, MATLAB, or similar algorithm development environments.
• Ability to communicate complex technical concepts effectively across engineering disciplines.

• Experience supporting FPGA‑based image processing architectures and hardware acceleration initiatives.
• Knowledge of GPU computing, parallel processing, and high‑performance computing techniques.
• Experience developing machine learning models for image classification, detection, segmentation, and anomaly detection.
• Familiarity with hyperspectral, multispectral, electro‑optical, infrared, or scientific imaging systems.
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