Computer Vision

Computer Vision & Multimodal LLMIntern (Drawing Change Analysis Agent)About DoazDoaz turns fragmented industrial knowledge into instant, actionable insight. We build LLM- and Vision-AI solutions for construction, heavy industry, and finance—helping teams convert drawings, specs, and regulations into real-time decisions. We’re expanding our GeoAI programs (incl. joint work with POSCO E&C) and launching drawing-change detection services that compare plan versions, detect deltas, and explain design impacts. Why You’ll Love Working HereShip real things: Your models and tools can reach production pilots in weeks. Mentorship, not bureaucracy: Learn directly from senior CV/LLM engineers and domain SMEs. Global crew: 30 teammates across KR/ PK/ IN ; English-first collaboration. Tech playground: YOLO/RT-DETR, Gemma-VL/Qwen-VL/LLaVA, PaddleOCR, LayoutLMv3, Triton—hands-on. Role OverviewAs a CV & Multimodal LLMIntern, you’ll support the end-to-end development of a version-aware drawing-diff engine (PDF/DWG raster & vector), symbol/text extraction, and change-impact narratives powered by RAG/LLM. You’ll prototype, evaluate, and iterate with fast feedback from real engineering users. What You’ll Do (Intern Scope)Drawing Change Analysis (CV): assist in rasterization, layer parsing, vector geometry ops; train/evaluate detectors (YOLOv8/RT-DETR/SAM); implement geometry-aware post-processing (IoU/topology/snapping). Document & Layout Understanding: combine OCR (PaddleOCR/Tesseract) with layout models (DocFormer/LayoutLMv3/Donut); normalize to structured JSON; help with version-aware entity tracking (gridlines, BH IDs, coordinates). GeoAI & LLM/RAG: set up retrieval (BM25 + vector with reranking); ground LLM answers with citations and clickable evidence; draft change-impact summaries with rule prompts + LLM verification. Productization Basics: package prototypes as FastAPI services or notebooks; write READMEs; contribute datasets, labeling guides, and simple A/B or ablation tests. Minimum QualificationsBS/MS student or recent graduate in CS/EE/CE/Geoinformatics/Civil (or similar). Solid Python (3.x); foundations in DS/algorithms, linear algebra, probability. Coursework/projects in CV and/or document AI (detection, segmentation, OCR, layout). Familiar with PyTorch or TensorFlow; Git, Linux, Jupyter. Clear written English; high learning velocity and ownership. Nice to HaveHands-on with YOLO/RT-DETR/Detectron2/SAM; PaddleOCR/Tesseract; LayoutLMv3/Donut. Exposure to VLMs (Gemma-VL, Qwen-VL, LLaVA), CLIP, rerankers. Experience with engineering drawings/CAD/PDF toolchains. Basic FastAPI, Docker, ONNX/TensorRT/Triton. Frontend (TypeScript/React) for quick review UIs. Internship Details & BenefitsType/Duration:Paid internship — 4 months (full-time preferred). Compensation (India):Stipend prorated from 6 LPA(INR600,000 annualized), paid monthly ( ≈ INR 50,000/monthduring the internship). For candidates outside India, compensation will bebenchmarked to local market equivalents. Conversion:High performers will receive a full-time offerupon successful completion of the 4-month internship. Perks: Mentorship, cloud/GPU credits, real production impact. Hiring Process (fast)Intro call (15–20 min). 48-hour mini task: simple drawing diff or OCR/layout extraction + short README (clarity > polish). Tech chat (45–60 min): approach, trade-offs, evaluation. Founder chat on culture & goals. Offer. How to ApplyEmaildoaz@doaz.ai with subject[CV/LLM Intern – Your Name]and include: Résumé/CV (highlight courses/projects; metrics if available). GitHub or demo links (CV/doc-AI/RAG preferred). Availability (start date, weekly hours). (Optional) A one-page diagram of your “Drawing Revision → Detection → Evidence → LLM Narrative” pipeline. Ready to learn fast and turn messy drawings into trusted intelligence? Join Doaz and build with us.