Computer Vision Engineer

Ryz Labs; Argentina; Remote; ARS 136,430,000 - 227,383,000; Full time

Job summary

Ryz Labs is partnering with a client building an AI-powered platform for automated quantity takeoff in heavy civil and highway construction. As a Senior Computer Vision / ML Engineer, you'll own the “what is it?” problem—identifying materials, surfaces, and construction features from drawings, PDFs, aerial imagery, and satellite imagery.

You’ll build CV/ML pipelines, extract information from PDFs, and develop detection and segmentation models for materials and infrastructure.

Qualifications

• 5+ years of production CV/ML experience.
• Strong Python and PyTorch experience.
• Production experience with detection and segmentation on real-world imagery.
• Experience with aerial, satellite, drone, or comparable raster imagery.
• Strong knowledge of OpenCV and classical CV techniques.
• Experience with messy, domain-specific data and human-in-the-loop systems.
• Understanding of PDF internals, vector geometry, and/or document AI, or the ability to learn quickly.
• Strong written and verbal English.

Responsibilities

• Build CV/ML pipelines for engineering drawings, PDFs, aerial and satellite imagery.
• Extract information from vector and raster PDFs, including degraded/scanned drawings.
• Develop detection and segmentation models for materials and infrastructure such as asphalt, concrete, pavement, drainage, pipes, signs, guardrails, and lane markings.
• Combine information from drawings, specifications, and imagery, identifying discrepancies between sources.
• Build the ML infrastructure around the models: labeling, datasets, evaluation, regression testing, confidence, and provenance.
• Work directly with domain experts to create ground truth and improve the system.
• Prioritize reliability and completeness— “not determinable” is better than a low-confidence guess.

Skills

Production CV/ML experience

Python

PyTorch

Aerial imagery experience

OpenCV

Document AI / PDF

English proficiency

Human-in-the-loop

Tools

Python

PyTorch

OpenCV

Job description

Contract directly with the client Remote - Full-time Only for candidates based in Latam.

We are looking for a Computer Vision Engineer. Ryz Labs is partnering with a client building an AI-powered platform for automated quantity takeoff in heavy civil and highway construction. As a Senior Computer Vision / ML Engineer, you'll own the “what is it?” problem—identifying materials, surfaces, and construction features from engineering drawings, PDFs, aerial imagery, and satellite imagery.

What You’ll Do

• Build CV/ML pipelines for engineering drawings, PDFs, aerial and satellite imagery.
• Extract information from both vector and raster PDFs, including degraded/scanned drawings.
• Develop detection and segmentation models for materials and infrastructure such as asphalt, concrete, pavement, drainage, pipes, signs, guardrails, and lane markings.
• Combine information from drawings, specifications, and imagery, identifying discrepancies between sources.
• Build the ML infrastructure around the models: labeling, datasets, evaluation, regression testing, confidence, and provenance.
• Work directly with domain experts to create ground truth and improve the system.
• Prioritize reliability and completeness— “not determinable” is better than a low-confidence guess.

What We’re Looking For

• 5+ years building and shipping production Computer Vision / ML systems.
• Strong Python and PyTorch experience.
• Production experience with detection and segmentation on real-world imagery.
• Experience with aerial, satellite, drone, or comparable raster imagery.
• Strong knowledge of OpenCV and classical CV techniques.
• Experience with messy, domain-specific data and human-in-the-loop systems.
• Understanding of PDF internals, vector geometry, and/or document AI, or the ability to learn quickly.
• Strong written and verbal English.

Nice to have

• Experience with geospatial imagery, construction, document AI/OCR, CAD vectorization, or autonomous vehicle perception.
• 3D experience with photogrammetry, point clouds, terrain/surface models, or cut & fill.
• Experience across both document vision and aerial/geospatial CV.