AI, Computer Vision Engineer

Computer Vision Engineer — Industrial AI Platform (Full-time)

Doaz Inc. | Seoul, Korea

About Doaz

Doaz transforms industrial expertise into actionable AI. We build vertical AI solutions for engineering-intensive industries—construction, shipbuilding, heavy industries, and geotechnical engineering—where precision, regulatory compliance, and domain knowledge are non-negotiable.

Our products are trusted by Korea’s leading enterprises, including POSCO E&C, Samsung Heavy Industries, Doosan Enerbility, and KT Estate . From automating geotechnical analysis with 95%+ accuracy to generating safety risk assessments in under 10 seconds , we solve problems that generic AI cannot reliably handle.

• Founded : 2023
• Team : 20+ engineers and domain experts
• Vision : Industrial Knowledge → Actionable AI

The Role

We’re looking for a Computer Vision Engineer to build the visual intelligence layer of our industrial AI platform. You will develop systems that understand engineering drawings, extract structured data from technical documents, and support automated verification across multiple industrial domains.

This is not a demo role. Our CV models run in production and process high-volume engineering documents. In our world, a 1% accuracy improvement can translate to massive reductions in engineering hours and downstream rework.

What You’ll Build

1) Drawing Intelligence

Object detection and instance segmentation for engineering drawings (architectural plans, structural drawings, P&IDs, ship block diagrams)

Symbol recognition across industrial standards (KS / ISO / ASME, classification society rules)

Extraction of relationships, cross-references, and revision changes across drawing sets

2) Document Understanding

Layout analysis for technical specs, engineering calculations, and regulatory documents

Table extraction from material schedules, BOMs, and equipment lists

Multi-format processing : PDF, scanned images, and CAD exports (DXF / DWG)

3) Compliance & Verification

Visual verification for compliance requirements (building codes, safety standards, maritime rules)

Automated comparison between design drawings and as-built documentation

Defect detection for construction / manufacturing quality inspection workflows

Domain Applications (Examples)

Construction : floor plan analysis, certification review support, finish schedule extraction

Shipbuilding : block drawing interpretation, piping diagram analysis, weld symbol recognition

Heavy Industries : equipment layout verification, safety zone compliance, P&ID digitization

Geotechnical : borehole log interpretation, geological profile visualization

What We’re Looking For

Required

3+ years in computer vision / deep learning with production deployment experience

MS or PhD in Computer Science, AI, or related field

Strong PyTorch proficiency; hands-on with detection / segmentation (YOLO / DETR / Mask R-CNN, etc.)

Strong Python engineering; comfortable with Git, Docker, and Linux environments

Ownership mindset; able to drive projects from research to production

Preferred

Document AI experience : OCR, layout analysis, table extraction (LayoutLM / Donut / PaddleOCR, etc.)

CAD / engineering drawing domain familiarity

Experience in regulated / industrial environments (construction / manufacturing / maritime)

Multimodal AI (Vision-Language Models) research or applied experience

MLOps : serving, monitoring, retraining pipelines

Publications or open-source contributions

Tech Stack (Typical)

Modeling : PyTorch, HuggingFace Transformers, Detectron2

Optimization : ONNX Runtime, TensorRT

CV : OpenCV, Albumentations

Document / OCR : PaddleOCR, Tesseract, LayoutLMv3, Donut, DocTR, PyMuPDF

Infra : AWS (EC2 / S3 / Lambda / SageMaker), Docker, Kubernetes

Data : PostgreSQL, Elasticsearch, Vector DBs (Pinecone / Milvus)

Collaboration : GitHub, Notion, Slack

Why Doaz

Solve real problems : Production systems used by real engineering teams

Deep technical work : Accuracy is a core product metric, not an afterthought

Domain expertise access : Work with engineers who have decades of field experience

Growth stage : Shape platform direction as we scale in Korea and expand globally

Compensation : Competitive salary + equity (impact-driven)

Interview Process

Application Review (Resume + Portfolio)

Take-home Technical Assessment (approx. 3 hours)

Technical Interview (review + deep dive, 60 min)

Apply

Email doaz@doaz.ai

with :

Resume / CV

Portfolio (GitHub, papers, or project documentation)

A brief note on why industrial AI interests you

We review applications weekly and respond to all candidates.

Doaz Inc. — Building AI that understands how industries actually work.