Computer Vision Engineer – Evaluation and Data Quality

We’re looking for a Computer Vision Engineer focused on evaluation and data quality to help improve the performance of real-world CV systems.

This role is centered around working with visual datasets, analyzing model outputs, and identifying failure patterns. You won’t be training models end-to-end — instead, you’ll play a key role in improving model quality through better data, validation, and structured analysis.

If you enjoy working hands-on with images and video data, spotting edge cases, and making systems more accurate and reliable — this role is for you.

What You’ll Do

• Review, annotate, and validate image and video datasets used in CV workflows
• Perform detailed error analysis on model outputs to identify weaknesses and edge cases
• Support evaluation workflows for tasks such as object detection, classification, segmentation, and pose estimation
• Improve data quality through structured labeling, annotation review, and consistency checks
• Help define evaluation criteria, benchmarks, and test datasets
• Collaborate with ML and CV engineers to provide clear feedback on model behavior
• Document findings, patterns, and recommendations
• Contribute to improving data pipelines and evaluation processes

What We’re Looking For

• 2+ years of experience in Machine Learning or Computer Vision
• Strong understanding of CV fundamentals and evaluation metrics
• Hands-on experience with image/video datasets, annotation, or CV model evaluation
• Familiarity with tasks such as object detection, classification, segmentation, or pose estimation
• Ability to analyze visual outputs and perform structured error analysis
• Strong Python skills
• Experience with tools or frameworks such as OpenCV, PyTorch, or TensorFlow
• High attention to detail and comfort with quality-focused work

Nice to Have

• Experience with multimodal or vision-language models
• Familiarity with tools like Labelbox, Scale AI, CVAT, or Roboflow
• Background in data-centric AI, visual QA, or dataset auditing
• Experience with 3D vision, depth estimation, or point cloud data
• Kaggle or CV competition experience

Why This Role

• Work on real-world computer vision systems and improve their accuracy
• Direct impact on model performance through data and evaluation
• High ownership over dataset quality and evaluation processes
• Collaborative and fast-moving engineering environment