About the Role
The role involves training artificial intelligence models using expertise in homography, ensuring accurate interpretation of image transformations and providing high-quality data inputs.
Responsibilities
- Analyze and interpret planar geometric transformations in visual data
- Train machine learning models to recognize and apply homography matrices
- Label and annotate image pairs with accurate transformation parameters
- Validate the correctness of estimated homography mappings
- Improve AI model performance through iterative feedback
- Identify edge cases in image alignment and perspective correction
- Ensure consistency in annotated datasets across multiple environments
- Collaborate with engineers to refine model training pipelines
- Document patterns in transformation errors for system improvement
- Maintain high accuracy standards in data labeling tasks
- Review output from automated homography estimation tools
- Flag ambiguous or low-quality image inputs
- Support quality assurance processes for visual data sets
- Adapt to evolving model requirements and labeling guidelines
- Communicate technical issues affecting model training
- Work with diverse image sources including aerial and ground-level views
- Apply understanding of camera perspective and projective geometry
- Contribute to training materials for homography-related tasks
- Monitor data drift in transformation patterns over time
- Assist in benchmarking model performance on homography tasks
Nice to Have
- Prior work in autonomous vehicles or robotics vision systems
- Hands-on experience with deep learning models for geometry estimation
- Exposure to stereo vision or structure-from-motion pipelines
- Background in photogrammetry or remote sensing
- Experience labeling data for AI training at scale
- Knowledge of RANSAC or other robust estimation methods
- Familiarity with evaluation metrics for homography accuracy
- Contributions to open-source computer vision projects
- Academic research in geometric computer vision
- Experience with data labeling platforms
Compensation
Competitive salary based on experience
Work Arrangement
Remote
Team
Collaborative team focused on AI model development and data quality
What You’ll Do
- Train AI models by providing accurate homography annotations on image pairs
- Evaluate the quality of predicted transformation matrices
- Support development of systems that rely on precise image alignment
- Identify limitations in current model performance related to perspective estimation
- Help refine training datasets to improve generalization across scenes
What We’re Looking For
- Candidates with hands-on experience in image transformation tasks
- Individuals who understand the practical challenges of real-world homography estimation
- People who can maintain precision while processing large volumes of visual data
- Those who can clearly articulate geometric inconsistencies in image pairs
- Applicants familiar with the role of homography in visual perception systems
Not available
