Computer Vision Engineer

Your Job

You know us already! We make Brawny® paper towels; Dixie® paper cups and plates; Angel Soft® bath tissue; enMotion® paper towel dispensers, DensGlass® gypsum board and Plytanium® plywood you see in your big box home improvement stores and much more! We employ about 35,000 people who want to make a positive difference in today's world by creating real long-term value for our customers.

We have an opportunity on the Data Science team at Georgia-Pacific's Collaboration & Support Center, located in Atlanta, GA.

We are looking for an experienced Computer Vision Engineer to join a team of Data Scientists and engineers to focus on providing support and solutions to our manufacturing operations with an emphasis on Computer Vision.

Working closely with business partners and engineers, our team supports operations through development and deployment of useful and scalable statistical, machine learning, and deep learning models that make our facilities safe, efficient, and optimal.

What You Will Do


* CV Solution Architecture: Design end-to-end computer vision solutions from the ground up, selecting the right approach across the full spectrum from classical image processing (filtering, morphology, geometric transforms) through to modern deep learning architecture.


* CV Pipeline Ownership: Design, train, and deploy object detection, segmentation, and classification models for defect detection, quality inspection, and worker safety monitoring in active manufacturing environments.


* Project Ownership: Own all aspects of CV projects end-to-end: problem framing, data collection strategy, annotation pipeline setup, preprocessing, model training, validation, deployment, and post-production monitoring.


* Dataset & Annotation Engineering: Build and maintain annotation workflows and dataset versioning practices to support iterative model improvement at scale.


* Production Inference: Develop and manage inference pipelines targeting edge hardware and cloud infrastructure, including latency optimization, throughput tuning, model drift alerting, and own retraining decisions and schedules to maintain model robustness.


* Systems Integration: Integrate CV models into existing manufacturing control systems and IoT sensor streams; collaborate with software and process engineers on system interfaces.


* Partnership: Develop and maintain relationships with key operations and engineering partners; translate physical manufacturing problems into tractable vision problems and communicate findings clearly.


* Pragmatic Delivery: Build toward minimum viable solutions that solve most of the problem; ship working systems that capture value, then iterate.

Perfection is reserved for safety-critical applications.

Who You Are (Basic Qualifications)


* Bachelor's Degree or higher in a field related to data science such as Engineering, Mathematics, Business Analytics, Statistics, Computer Science or Data Science


* Proven expe...