Computer Vision Expert

Weekday AI

3d•$80 - $110•Remote

About The Position

Join a cutting-edge AI research initiative and help shape the next generation of frontier AI models. We are seeking experienced Computer Vision Experts to serve as subject matter experts, designing challenging real-world vision tasks, creating high-quality reference solutions, and evaluating AI model performance. Your work will directly improve AI systems by identifying reasoning gaps and advancing their capabilities across a wide range of computer vision applications.

Requirements

Deep hands-on experience in Computer Vision through industry, research, or graduate/PhD-level work.
Strong proficiency in Python with practical experience developing computer vision applications.
Expertise in modern computer vision techniques, including deep learning architectures and model evaluation.
Hands-on experience with frameworks such as PyTorch, TensorFlow, or similar computer vision libraries.
Solid understanding of computer vision workflows, model training, evaluation metrics, and optimization techniques.
Ability to commit approximately 20 hours per week.
Excellent written communication skills and the ability to work independently in a remote environment.

Nice To Haves

Experience in AI model evaluation, AI training data development, or data annotation.
Familiarity with multimodal AI systems, vision-language models, or generative AI applications.
Experience developing evaluation pipelines, automated testing frameworks, or benchmarking tools.
Contributions to open-source computer vision projects or published research are a plus.
Experience with large-scale production computer vision systems.

Responsibilities

Design challenging, real-world computer vision tasks across domains such as: Object Detection, Image Segmentation, Object Recognition, Vision-Language & Multimodal Reasoning, Image and Video Generation.
Develop high-quality reference solutions and integrate tasks into agentic development environments using Python.
Build executable evaluation components and testing frameworks where applicable.
Assess AI model outputs for accuracy, reasoning quality, and technical correctness.
Identify capability gaps, classify failure modes, and provide detailed written analyses of model behavior.
Develop evaluation guidelines and structured rubrics to ensure consistent and objective assessment.
Collaborate with fellow subject matter experts to maintain high-quality training data and evaluation standards.