Video Annotation & OCR Project – Remote (On-site/Nigeria)

Job Overview

In a landscape where machines are taught not merely to see but to interpret, we are in pursuit of Image Reinforcement Learning specialists who can refine the cognitive depth of visual AI systems. This opportunity revolves around shaping intelligent models that do more than recognize imagery they reason, adapt, and evolve through structured learning paradigms.

Reponsibilities

Architect and deploy reinforcement learning methodologies tailored to image-centric problem spaces, enabling models to iteratively improve through feedback-driven cycles.
Curate and construct high-quality training datasets alongside rigorous evaluation benchmarks that challenge and refine visual AI systems.
Dissect model behavior to uncover inefficiencies, then recalibrate performance across image recognition and visual reasoning tasks.
Engage with machine learning pipelines spanning classification, object detection, and segmentation—ensuring seamless operational flow.
Collaborate with AI researchers and engineers to amplify model precision, sharpening both inference quality and decision-making logic.
Produce structured, intelligible documentation capturing workflows, dataset architecture, and evaluation mechanics.

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Requirements

Academic grounding in Computer Science, Artificial Intelligence, Machine Learning, or a closely aligned discipline (Bachelor’s or Master’s level).
Demonstrable expertise in Reinforcement Learning, with the ability to translate theory into applied systems.
Practical immersion in Computer Vision and image processing techniques, with a nuanced grasp of visual data intricacies.
Proficiency in Python as the primary development language.
Hands-on familiarity with leading machine learning frameworks such as PyTorch and TensorFlow.
Experience leveraging OpenCV for image manipulation and processing workflows.
Solid understanding of deep learning architectures tailored for image interpretation and analysis.