Embedded Software Engineer (Image Processing Algorithms)

Description

Responsibilities

• Develop onboard computer vision algorithms for image preprocessing, thresholding, filtering, centroiding, feature extraction, target detection, target tracking, optical navigation, star detection, and attitude or pose estimation support. 
• Support image conditioning techniques such as calibration, distortion correction, dark-frame correction, thresholding, exposure control, filtering, and image normalization. 
• Work with GNC, flight software, and mission teams to define algorithm performance requirements, including accuracy, latency, update rate, robustness, fault tolerance, and compute/resource constraints. 
• Develop test tools, simulation environments, and analysis scripts to evaluate algorithm performance using synthetic imagery, lab imagery, ground test data, and flight-like datasets. 
• Debug and tune vision software during sensor bring-up, ground testing, environmental testing, and in-flight operations. 
• Contribute to fault detection, robustness, and recovery logic for cases such as poor lighting, stray light, saturation, blur, dropped frames, hot pixels, occlusions, image noise, and unexpected scene content. 
• Design algorithms and data pipelines that operate within constrained CPU, memory, storage, bandwidth, timing, and power budgets. 

Minimum Qualifications

• Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or related technical field.
• 2+ years of experience writing C++ code for embedded systems, preferably in imaging or robotic applications. 
• Experience implementing image processing, estimation, numerical, or signal processing algorithms. 
• Experience with bare-metal or RTOS-based software development. 

Preferred Skills and Experience

• Ability to work closely with hardware, flight software, GNC, and test teams to diagnose issues across software, sensors, timing, image quality, and system interfaces. 
• Experience optimizing software for runtime, memory usage, deterministic execution, and numerical stability. 
• Familiarity with low-level hardware interfaces such as SPI, I2C, UART, GPIO, timers, ADCs, DMA, and camera or image sensor interfaces. 
• Strong understanding of linear algebra, coordinate frames, rotations, quaternions, camera models, or geometric vision concepts. 
• Experience debugging embedded systems using oscilloscopes, logic analyzers, hardware debuggers, source-level debuggers, logs, and telemetry. 
• Hands-on experience developing or testing computer vision, optical navigation, star tracker, pose estimation, target tracking, inspection, or perception algorithms on microcontroller-class hardware.