Job Description

SiLC is a deep tech company with an immediate opening for a full-time on-site Software Engineer to be a part of a dynamic team focused on building a revolutionary 4D sensing solution. This person will be responsible for the development and testing of advanced point cloud processing algorithms for FMCW LiDAR-based applications. The ideal candidate will have experience with real-time programming, 3D computer vision, and the ability to transition algorithms from research prototypes to production-ready solutions. The candidate should have strong communication skills as he or she will interface with our development team leads and senior management. 

Key Responsibilities: 

• Design and implement point cloud processing algorithms for defect detection and identification in industrial environments 
• Create accurate dimensional measurement algorithms for 3D objects using 3D point cloud data 
• Develop robust volume calculation systems for regular/irregular objects using 3D point cloud data 
• Develop real-time 3D visualization using OpenGL and QT for point clouds 
• Contribute to and maintain our existing codebase 
• Code documentation 
• Participate in code reviews/technical discussions 

Required Qualifications: 

• MS degree in Computer Science, Electrical Engineering, or related field, with relevant experience 
• Strong programming skills in C/C++ 
• Python programming for rapid prototyping and algorithm development (NumPy, SciPy) 
• Familiarity with linear algebra and 3D geometry algorithms (surface reconstruction, clustering, segmentation) 
• Knowledge of multi-threading and concurrent programming paradigms 
• Experience with build systems (CMake, Make) and proficiency with version control systems (Git) 
• Excellent problem-solving abilities 
• Strong communication skills and ability to work in a team environment 

Nice to Haves: 

• Experience with CUDA or OpenCL for GPU acceleration 
• Familiarity with PCL/OpenCV libraries 
• Knowledge of ROS for robotics applications 
• Coursework in Computational Geometry and Machine Learning 
• Experience with ML/DL libraries such as sci-kit learn and PyTorch 
• Understanding of LiDAR sensor technologies and characteristics 
• Knowledge of metrology and precision measurement techniques 
• Knowledge of coordinate system transformations and calibration procedures 
• Understanding of sensor fusion techniques combining LiDAR with other sensors 

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