Company is a Dallas-based R&D and consulting firm specializing in Computer Vision & AI technology. We empower organizations to solve complex problems through AI-enabled actionable insights. Our approach emphasizes unique computer vision applications, retrofitting AI into existing workflows, driving long-term innovation, and delivering high-value, low-cost AI solutions. We focus on crafting highly creative AI approaches that provide sustainable and impactful results across various industries.
Job Description
Join us as a Computer Vision Engineer/Developer, where you will contribute to developing and deploying advanced computer vision solutions. This role involves implementing AI models, optimizing performance, and integrating solutions across various applications, including handling real-time RTSP camera feeds.
Responsibilities
- Develop and implement computer vision algorithms for tasks such as object detection, classification, and multi-object tracking.
- Work with RTSP camera feeds to enable real-time video processing and analysis.
- Optimize AI models for deployment on edge devices and cloud platforms.
- Integrate computer vision solutions into existing systems and workflows.
- Troubleshoot and resolve issues related to computer vision model deployment and performance.
- Stay up to date with the latest advancements in computer vision and AI to continuously improve solutions.
Minimum Requirements
- Fluent in Python; proficiency in C++ is a plus.
- Expert in computer vision libraries such as OpenCV, Scikit-Image, and PIL.
- Experience with RTSP camera feeds and real-time video streaming.
- Expert in machine learning platforms like PyTorch and/or TensorFlow.
- Familiar with object detection, classification, and multi-object tracking models and algorithms.
- Experience with CUDA for GPU-accelerated computing.
- Solid background in traditional computer vision techniques, such as camera calibration, feature extraction, and movement analysis.
- Understanding of why tools and algorithms work, not just how to use them.
Preferred Qualifications
- Bachelor's or master's degree in computer science or a related field.
- Familiarity with cloud computing services (AWS, Azure, Google Cloud).
- Experience in model optimization techniques (quantization, pruning).
- Knowledge of edge computing and embedded systems.