Senior Computer Vision Engineer ID72408

AgileEngine•Houston, TX

11d•Onsite

About The Position

AgileEngine is seeking a Senior Computer Vision Engineer to own applied model development across computer vision, machine learning, and data science use cases. The role involves building and deploying solutions for object detection, image segmentation, classification, and video analysis; evaluating and fine-tuning model architectures using PyTorch and TensorFlow; developing broader machine-learning models for forecasting and anomaly detection; and applying practical knowledge of computer-vision hardware, including cameras, sensors, and edge devices. Engineers located in the US must reside in Dallas, Texas, and be open to working onsite from the office. The role also offers flexible scheduling with remote and office options.

Requirements

Must be authorized to work for any employer in the United States; the company cannot sponsor or take over employment visa sponsorship.
3 to 5 years of professional experience in computer vision, machine learning, data science, or a related field.
Degree in computer science, engineering, data science, mathematics, or a related discipline, or equivalent practical experience.
US-based engineers must reside in Dallas, Texas, and be open to working onsite from the office.
Strong, production-level proficiency in Python.
Deep hands-on experience with PyTorch and/or TensorFlow.
Proven experience building and deploying models for detection, segmentation, classification, and image/video analysis.
Solid understanding of machine-learning and data-science techniques, including time-series modeling, forecasting, anomaly detection, regression, and clustering.
Practical experience with computer-vision hardware, including cameras, sensors, and lighting setups.
Familiarity with deploying models on edge devices.
Strong understanding of how physical and real-world constraints affect data quality, model training, and inference.
Upper-intermediate English level.

Responsibilities

Own applied model development across computer vision, AI/ML, and broader data science use cases.
Translate complex business problems into viable, practical, and scalable AI/ML solutions.
Evaluate model options, train and fine-tune selected architectures, and rigorously analyze model performance.
Develop and deploy solutions for object detection, image segmentation, image classification, and video analysis.
Build and maintain models for time-series forecasting, anomaly detection, regression, clustering, and general data analysis.
Account for real-world constraints, including lighting, sensor limitations, and edge-device compute power, to ensure high data quality and robust production model performance.