Remote position within Argentina or Uruguay
RYZ Labs is looking for a highly skilled Computer Vision Engineer to collaborate on cutting-edge AI solutions that transform the global supply chain. You’ll work with a forward-thinking client to develop AI-powered vision systems that analyze real-world logistics operations, enabling intelligent automation, real-time insights, and advanced object recognition through computer vision, OCR, and deep learning. This is a unique opportunity to apply your expertise in AI and machine learning to solve high-impact challenges in a rapidly evolving industry.
Basic Qualifications: - Strong proficiency in Python and deep learning frameworks like PyTorch.- Hands-on experience with YOLO (v8, v11, or similar) for object detection.- Experience with OpenCV for image processing and feature extraction.- Practical knowledge of OCR technologies such as Tesseract, EasyOCR, or commercial APIs.- Understanding of model training, evaluation, and optimization for real-world deployment.- Familiarity with active learning workflows to improve model performance over time.- Experience with hybrid edge + cloud architectures for deploying vision models.- Strong problem-solving skills and ability to work in a fast-paced, evolving environment.
Key Responsibilities:- Develop and optimize computer vision models for real-time vehicle recognition, OCR, and object tracking.- Design and implement hybrid edge + cloud architectures for scalable, low-latency inference.- Train and deploy YOLO-based object detection models in real-world applications.- Build active learning workflows to continuously improve model accuracy.- Use OpenCV and deep learning frameworks to process and extract structured data from images and video.- Optimize model performance for deployment on edge devices and cloud environments.- Work with software engineers to integrate models into scalable production systems.- Experiment with new computer vision techniques to push the boundaries of automation in logistics.
Nice to have:- Experience with tracking objects across multiple cameras for persistent identification.- Knowledge of coordinating PTZ (pan-tilt-zoom) cameras for automated tracking.- Experience deploying and optimizing models on edge hardware.- Familiarity with cloud-based machine learning workflows (Google Cloud, AWS, or Azure).
About RYZ Labs:
RYZ Labs is a startup studio built in 2021 by two lifelong entrepreneurs. The founders of RYZ have worked at some of the world's largest tech companies and some of the most iconic consumer brands. They have lived and worked in Argentina for many years and have decades of experience in Latam. What brought them together is the passion for the early phases of company creation and the idea of attracting the brightest talents in order to build industry-defining companies in a post-pandemic world.
Our teams are remote and distributed throughout the US and Latam. They use the latest cutting-edge technologies in cloud computing to create applications that are scalable and resilient. We aim to provide diverse product solutions for different industries, planning to build a large number of startups in the upcoming years.
At RYZ, you will find yourself working with autonomy and efficiency, owning every step of your development. We provide an environment of opportunities, learning, growth, expansion, and challenging projects. You will deepen your experience while sharing and learning from a team of great professionals and specialists.
Our values and what to expect:- Customer First Mentality - every decision we make should be made through the lens of the customer.- Bias for Action - urgency is critical, expect that the timeline to get something done is accelerated.- Ownership - step up if you see an opportunity to help, even if not your core responsibility. Humility and Respect - be willing to learn, be vulnerable, and treat everyone who interacts with RYZ with respect.- Frugality - being frugal and cost-conscious helps us do more with less.- Deliver Impact - get things done in the most efficient way.- Raise our Standards - always be looking to improve our processes, our team, and our expectations. The status quo is not good enough and never should be.
