Senior Computer Vision Engineer

Job title: Senior Computer Vision Engineer

About the Role We are looking for a Senior Computer Vision Engineer to own applied model development across computer vision, ML, and broader data science use cases — building and deploying solutions for object detection, image segmentation, classification, and video analysis. You will evaluate and fine-tune model architectures using PyTorch and TensorFlow, and apply practical knowledge of computer vision hardware including cameras, sensors, and edge devices to ensure robust production performance.

What You'll Do

• Own the applied model development process across computer vision, AI/ML, and 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.
• Apply practical knowledge of real-world constraints—such as lighting, sensor limitations, and edge device compute power—to ensure optimal data quality and robust model performance in production.

What We're Looking For

• 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).
• Engineers located in the US must reside in Dallas, TX, and be open to working from the office (onsite).
• Strong, production-level proficiency in Python.
• Deep hands-on experience with leading deep learning frameworks, specifically PyTorch and/or TensorFlow.
• Proven track record of building and deploying models for detection, segmentation, classification, and image/video analysis.
• Solid understanding of broader ML and data science techniques (time-series modeling, forecasting, anomaly detection, regression, and clustering).
• Upper-intermediate English level.

Nice to Have

• Practical experience working 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 impact data quality, model training, and inference.

Compensation & Benefits

• Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
• Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
• A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
• Flextime: Tailor your schedule for an optimal work-life balance, with options of working from home and going onsite as needed.