Computer Vision Specializations
Computer vision is broad. Identify which sub-specialty you need before hiring. Object detection and tracking engineers work with YOLO, Detectron2, and similar frameworks for real-time detection. Image classification engineers build models for categorizing images at scale. Medical imaging specialists apply deep learning to X-rays, MRIs, and pathology slides. Video analysis engineers work with temporal models for action recognition and anomaly detection.
Core Skills to Evaluate
Fundamentals
Every computer vision engineer should know: convolutional neural networks and modern architectures (ResNet, EfficientNet, Vision Transformers), image preprocessing and augmentation techniques, transfer learning and fine-tuning for domain-specific tasks, OpenCV for image manipulation and processing, and evaluation metrics (mAP, IoU, precision-recall for detection tasks).
Production Skills
For production roles, also evaluate: model optimization (quantization, pruning, distillation), edge deployment experience (ONNX, TensorRT, CoreML), real-time inference optimization, data pipeline design for image and video processing, and experience with annotation tools and quality management.
Technical Assessment
Provide a dataset and a well-defined task (detect objects in images, classify medical images, etc.). Evaluate not just model accuracy but also: their data exploration and preprocessing approach, training methodology and hyperparameter tuning, error analysis and model debugging, and inference speed and deployment considerations.
Market Rates
US computer vision engineers earn $145K-$210K annually. LatAm rates range from $5,000-$7,500/month. Specialists in medical imaging or autonomous vehicle perception command premium rates in both markets. Latin America has strong computer vision talent coming from university research programs in Brazil, Mexico, and Argentina.
Hiring Through South
South screens computer vision candidates with practical assessments tailored to your use case. We verify production deployment experience, not just Kaggle leaderboard performance. Our candidates are ready to contribute to your CV pipeline from week one.
