Description:
Doaz is seeking a highly skilled Senior AI Engineer with a Master’s degree (or higher) in Computer Science, Electrical Engineering, AI, or a related field. You will lead the design, development, and deployment of our next‑generation drawing‑management SaaS platform, focused on:
- Automated content recognition within engineering drawings (floor plans, sections, structural details, rebar schedules, column schedules, etc.)
- Metadata extraction and standardization
- AI‑powered classification and grouping by purpose, function, and spatial domain
- LLM/RAG‑based natural‑language search and industrial drawing recommendation
Key Responsibilities
- Content Recognition & Extraction
- Architect and implement deep‐learning models for object detection/segmentation (e.g., VLMs, YOLO, Detectron2, U‑Net) to identify industrial drawing regions.
- Integrate OCR solutions (Tesseract, Google Vision API, or custom TensorFlow/Keras pipelines) for text and annotation extraction.
- Standardize extracted metadata into JSON/XML formats and validate against industry schemas (IFC/BIM).
- Data Pipeline & Storage
- Design scalable data ingestion and preprocessing pipelines for mixed‐media drawing formats (PDF, JPEG, DWG).
- Build and maintain a hybrid data store:
- Relational DB (PostgreSQL) for structured metadata
- Graph DB (Neo4j) to model inter‑drawing relationships
- Vector database (FAISS, Pinecone, or Qdrant) for embedding‐based similarity search
- Classification & Grouping
- Develop and train machine‐learning/deep‐learning classifiers (SVM, Random Forest, or neural networks) to automatically group drawings by purpose, function, and space.
- Implement clustering algorithms (K‑means, DBSCAN) to refine grouping based on evolving data patterns.
- LLM & RAG Integration
- Integrate and fine‑tune large language models (GPT‑3/4, Llama or equivalent) for domain‑specific query understanding.
- Construct a robust RAG pipeline: vector search → retrieval of relevant metadata → LLM‑augmented response generation.
- Optimize end‑to‑end latency to ensure sub‑3‑second response times.
- API & Front‑End Prototyping
- Develop RESTful APIs (FastAPI or Flask) exposing search, classification, and metadata services.
- Collaborate with front‑end engineers to build a Streamlit (or equivalent) prototype showcasing:
- Drawing search by natural language
- Interactive recommendation panels
- Graph‑network visualization of drawing relationships
- Collaboration & Documentation
- Drive daily stand‑ups, design reviews, and code reviews.
- Produce clear technical documentation, API specs, and user guides.
- Mentor junior engineers and contribute to knowledge‑sharing sessions.
Required Qualifications
- Master’s degree or higher in Computer Science, AI, Machine Learning, or a closely related technical field.
- 3+ years of professional experience in AI/ML engineering, with a strong portfolio of computer vision and NLP projects.
- Proficiency in Python and deep‑learning frameworks (TensorFlow, PyTorch).
- Hands‑on experience with object detection/segmentation (e.g., YOLO, Detectron2).
- Solid understanding of OCR technologies and text‐extraction pipelines.
- Experience designing and querying relational (PostgreSQL) and graph databases (Neo4j).
- Familiarity with vector databases for embedding search (FAISS, Pinecone, Qdrant).
- Practical exposure to LLMs and building RAG systems.
- Strong software engineering skills: API development, containerization (Docker), version control (Git).
- Excellent problem‑solving skills, attention to detail, and ability to work in a fast‑paced, agile environment.
- Fluent English communication skills (both written and verbal).