SENIOR COMPUTER
VISION ENGINEERS

Built for Production Ready Vision AI.

Square Codex helps North American companies hire experienced nearshore Computer Vision Engineers from Costa Rica and Latin America who can design, train, optimize, and deploy AI systems that understand images, video, objects, scenes, and visual data.

Our Computer Vision Engineers can work across image processing, object detection, segmentation, classification, tracking, model evaluation, data annotation pipelines, real-time inference, edge deployment, and production-ready vision AI workflows.

WHAT OUR COMPUTER VISION ENGINEERS BRING

Vision AI Expertise

Experienced engineers who understand image processing, deep learning, object detection, segmentation, classification, tracking, and real-world computer vision systems.

Production Model Deployment

Professionals who can move computer vision models from experimentation into scalable production environments with monitoring, optimization, and deployment support.

Nearshore Alignment

Computer Vision talent from Costa Rica and Latin America working in compatible time zones with North American companies.

Model Quality and Performance

We focus on accuracy, latency, data quality, inference performance, model validation, and maintainable vision AI workflows.

COMPUTER VISION TALENT FOR REAL WORLD AI APPLICATIONS

Whether you need image recognition, video analytics, object detection, visual inspection, segmentation, tracking, OCR, 3D vision, or real-time inference, Square Codex can help you identify the right senior Computer Vision Engineer for your product and technical environment.

Senior Computer Vision Engineers
Computer Vision AI Engineers
Deep Learning Engineers
Image Processing Engineers
Video Analytics Engineers
Object Detection Engineers

Segmentation Engineers
3D Computer Vision Engineers
OCR Engineers
Edge AI Engineers
Vision MLOps Engineers
AI Model Optimization Engineers

PRODUCTION READY COMPUTER VISION FOR MODERN AI TEAMS

Our Computer Vision Engineers are not only familiar with models and datasets. They understand the engineering work required to turn visual AI into reliable software, including data preparation, annotation workflows, model training, evaluation, deployment, monitoring, and performance optimization.

From Python, PyTorch, TensorFlow, OpenCV, YOLO, Detectron2, ONNX, TensorRT, Docker, and cloud platforms to edge deployment and real-time inference, our engineers know how to build vision AI systems that can operate beyond the prototype stage.

The result is a computer vision team that can help companies analyze visual data, automate image and video workflows, improve product intelligence, and support AI systems with production-level performance.

CORE COMPUTER VISION CAPABILITIES FOR MODERN AI PRODUCTS

Senior Computer Vision Engineers are expected to do more than train models. They help companies define visual AI use cases, prepare image and video datasets, build model workflows, evaluate performance, optimize inference, and deploy computer vision systems into real production environments.

Square Codex can help you find Computer Vision talent with experience across Python, PyTorch, TensorFlow, OpenCV, object detection, segmentation, image classification, tracking, annotation pipelines, MLOps, cloud deployment, edge AI, and real-time inference.

Object Detection and Recognition

Build models that identify, locate, and classify objects within images or video streams. This can include use cases such as visual search, safety monitoring, inventory detection, manufacturing inspection, retail analytics, and product intelligence.

Image Segmentation and Classification

Develop models that classify images or separate visual elements at the pixel or object level. Senior Computer Vision Engineers can support semantic segmentation, instance segmentation, medical imaging, quality control, and detailed scene understanding.

Video Analytics and Tracking

Create systems that analyze video data over time, track objects or people, detect motion patterns, identify events, and support real-time visual monitoring workflows.

Data Annotation and Dataset Quality

Support the full lifecycle of image and video datasets, including data collection, labeling strategy, annotation quality, augmentation, dataset curation, bias review, and training data preparation.

Model Optimization and Real-Time Inference

Improve model performance for production environments by optimizing accuracy, latency, throughput, memory usage, and inference speed. This can include ONNX, TensorRT, GPU acceleration, edge deployment, and model compression.

Computer Vision MLOps and Deployment

Move computer vision models into production using repeatable processes for versioning, experiment tracking, CI/CD, monitoring, rollback planning, cloud deployment, edge deployment, and production troubleshooting.

How We Help You Hire Better

Understand the Vision AI Need

We review your product goals, visual data sources, image or video workflows, model requirements, deployment environment, latency needs, and technical constraints before recommending talent.

Match for Technical Fit

We focus on senior Computer Vision Engineers who align with your tools, model architecture, data pipelines, cloud platforms, edge requirements, and delivery goals.

Support the Integration

We stay involved through onboarding and follow up to help the Computer Vision Engineer integrate successfully with your AI, data, product, engineering, and MLOps teams.