Senior Cv / Llm Engineer
doAZAjmer, Republic Of India, IN14 days ago
Job descriptionTrue 0-to-1 ownership — Ship models that land in production sites within weeks. Global impact, lean crew — 30 teammates across KR🇰🇷 / PK🇵🇰 / IN🇮🇳; Tech freedom — YOLO or RT-DETR? Gemma-VL, Qwen-VL, or LLaVA? You choose, we fund. Build a robust diff pipeline for architectural / structural / MEP drawings : rasterization, layer parsing, vector geometry ops, and semantic change clustering. Train / finetune detectors & segmenters (e.G., YOLOv8 / RT-DETR / Detectron2 / SAM) for symbols (columns, openings, sleeves), title blocks, and revision clouds; Implement geometry-aware post-processing (IoU / topology checks, snapping, graph connectivity) to reduce false positives. Engineer OCR + layout models (PaddleOCR / Tesseract + DocFormer / LayoutLMv3 / Donut) to read legends, notes, schedules, and BOM tables; Build version-aware entity tracking (IDs, gridlines, BH IDs, coordinates) across revisions. Design retrieval over drawings / specs (BM25 + vector) with reranking; Generate change-impact summaries (e.G., slab shear reinforcement, opening proximity to columns) with rules + LLM verification; Ship FastAPI / gRPC microservices, batch & streaming workers (Ray / Celery), GPU inference (Triton / TensorRT), and observability (Prometheus / Grafana). Own evaluation : dataset curation, data labeling guidelines, ablation / A-B tests, and regression suites. Work closely with domain SMEs (geotech / structural) to encode rules (KDS / KBC, internal standards) and prioritize what matters to the field. 5+ years of production Python (3.X) building ML-heavy backends; 3+ years in computer vision for detection / segmentation / OCR or document AI at scale. Hands-on with multimodal LLM / RAG (LangChain / LlamaIndex), vector DBs (Pinecone / Weaviate / FAISS), and rerankers. Proven experience parsing engineering drawings or complex PDFs (vector / raster), including geometry and layout reasoning. Solid MLOps : reproducible training, CI / CD, model packaging, monitoring; Fluent written & spoken English (Korean a plus). GPU orchestration (Kubernetes / Ray / Slurm), high-performance inference (ONNX / TensorRT). Experience with VLMs (Gemma-VL, Qwen-VL, LLaVA), CLIP, or doc-layout models. Open-source contributions, papers, or strong public demos in CV / doc AI / RAG. Full-stack chops (TypeScript / Next.Js / React) for quick operator tools and review UIs. Competitive base salary (market-leading), around 20 lakh (yearly) Performance-based annual bonus (up to 20%). cloud credits, and AI tools support. Quick intro call (15 min, mutual fit). 48-hour take-home : Drawing Diff + Evidence-Grounded Summary (provide code + short README; Deep-dive tech interview : architecture, modeling choices, evaluation, and scaling plan. Culture & vision chat with Founder / CEO. Offer — if all green, written offer within 24 h. Résumé / CV with measurable outcomes (metrics, latency, cost, accuracy). Current or recent salary. GitHub and / or live demos of CV / doc-AI / RAG work (links preferred). A one-page diagram of your “Drawing Revision → Detection → Evidence → LLM Narrative” pipeline, noting models, retrieval, and evaluation metrics.
Job description
About Doaz
- Doaz is a hyper-growth startup on a mission to turn fragmented industrial knowledge into instant, actionable insight. We build LLM- and Vision-AI solutions for construction, heavy industry, and finance leaders who must transform terabytes of drawings, specifications, and regulations into real-time decisions.
- We’re expanding our GeoAI programs (including joint work with POSCO E&C) and launching drawing-change detection services that automatically compare plan versions, detect deltas, and explain design impacts.
Why You’ll Love Working Here
no bureaucracy, only builders.
Role Overview
We’re hiring a Senior Computer Vision & Multimodal LLM Engineer (GeoAI & Drawing Change Analysis).
You’ll lead 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. Expect fast cycles from prototype → service : detection models, OCR / layout understanding, retrieval, and explainable outputs that engineers can trust.
Key Responsibilities
Drawing Change Analysis (CV)
achieve production-grade mAP / F1.
Document & Layout Understanding
normalize to structuredJSON.
GeoAI & LLM / RAG
ground LLM answers in evidence with citations and clickable locations.
measure factual precision.
Productization & DevOps
Collaboration
Minimum Qualifications
strong PyTorch.
cloud on AWS / GCP.
Preferred Extras
Compensation & Benefits
Hiring Process (≈ 2–3 weeks)
clarity >
polish).
How to Apply
Email doaz@doaz.ai with subject [CV / LLM Engineer – Your Name] and include :
Employment type : Full-time
Ready to turn messy drawings and specs into instant, trusted intelligence?
Let’s build the future together at Doaz.
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Senior Engineer • Ajmer, Republic Of India, IN
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