Senior Computer Vision Engineer - Remote-friendly Edge AI

AgileEngine, LLC.; Plano (TX); On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Professional growth

Competitive compensation

Exciting projects

Flextime

Job summary

AgileEngine, LLC. is seeking a Senior Computer Vision Engineer to own applied model development across CV, ML, and data science use cases, building and deploying solutions for object detection, segmentation, classification, and video analysis.

You will evaluate architectures with PyTorch and TensorFlow, develop broader ML models, and apply knowledge of cameras, sensors, and edge devices to production-ready systems in the US.

Qualifications

• 3–5 years of professional experience in Computer Vision, ML, Data Science or related field.
• US work authorization; no visa sponsorship.
• Strong proficiency in Python.
• Experience with PyTorch and/or TensorFlow.
• Proven track record delivering models for detection, segmentation, classification, and video analysis.

Responsibilities

• Own the applied model development process 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 architectures, and analyze performance.
• Develop and deploy solutions for object detection, image segmentation, classification, and video analysis.
• Build and maintain models for time-series forecasting, anomaly detection, regression, clustering, and general data analysis.

Skills

Python

PyTorch

TensorFlow

Computer Vision

Machine Learning

Data Science

Edge devices

Image/video analysis

Education

Bachelor's or higher in Computer Science/Engineering/Data Science

Job description

AgileEngine, LLC. is seeking a Senior Computer Vision Engineer to own applied model development across CV, ML, and data science use cases, building and deploying solutions for object detection, segmentation, classification, and video analysis.

You will evaluate architectures with PyTorch and TensorFlow, develop broader ML models, and apply knowledge of cameras, sensors, and edge devices to production-ready systems in the US.