Computer Vision & ML Expert

Computer Vision & ML Expert (AI Training)
About The Role

What if your expertise in computer vision could directly shape how the next generation of AI systems perceives, interprets, and understands the visual world? We're looking for Computer Vision & Machine Learning Experts to evaluate, improve, and guide AI models that process images, video, and visual data — helping build systems that truly see.
• This is a fully remote, flexible contract role for practitioners with hands-on experience in computer vision and machine learning. Whether you're a researcher, engineer, or advanced graduate student, your technical depth will have a direct, measurable impact on AI systems used by millions.
• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 10–40 hours/week
• What You'll Do
• Evaluate AI-generated outputs related to image recognition, object detection, segmentation, and visual reasoning tasks
• Assess the quality, accuracy, and robustness of computer vision model predictions and outputs
• Identify failure modes, edge cases, and biases in visual AI systems
• Create, review, and refine training data annotations for computer vision pipelines
• Provide expert-level feedback on model behavior, architecture decisions, and output quality
• Write detailed technical evaluations and suggest concrete improvements
• Work across diverse visual domains — from natural images and medical imaging to autonomous systems and document understanding
• Complete task-based assignments independently on your own schedule
• Who You Are
• Strong foundational knowledge of computer vision — object detection, image classification, semantic segmentation, pose estimation, or related areas
• Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX
• Familiarity with common CV architectures (CNNs, Vision Transformers, diffusion models, etc.)
• Comfortable reading and understanding ML research papers
• Solid understanding of data preprocessing, augmentation, and annotation best practices for visual data
• Detail-oriented and systematic in evaluating model outputs
• Clear, concise written communicator who can explain technical concepts effectively
• Self-motivated and reliable when working independently
• Nice to Have
• MS or PhD in Computer Science, Electrical Engineering, or a related field with a focus on computer vision or machine learning
• Published research in top CV/ML venues (CVPR, ICCV, ECCV, NeurIPS, ICML, etc.)
• Experience with 3D vision, video understanding, generative models, or multimodal AI
• Familiarity with MLOps tools, experiment tracking, and model evaluation pipelines
• Background in specialized domains such as medical imaging, remote sensing, robotics, or autonomous driving
• Experience with annotation platforms and data quality workflows at scale
• Proficiency in Python and scientific computing libraries (NumPy, OpenCV, scikit-learn)
• Why Join Us
• Work on cutting-edge AI projects alongside leading research labs
• Fully remote and flexible — work when and where it suits you
• Freelance autonomy with the structure of meaningful, task-based work
• Make a direct, tangible impact on how AI systems perceive and interpret the visual world
• Engage with diverse, challenging problems across multiple visual domains
• Potential for ongoing work and contract extension as new projects launch
• Join a global community of top-tier AI practitioners shaping the future of machine intelligence