AI/ML Engineer - Architectural Drawing Understanding (US)

Genia; Los Angeles (CA); On-site; USD 100,000 - 140,000; Full time

Benefits offered by this job

Competitive compensation package

Equity incentives

Job summary

A generative AI company in Los Angeles seeks an AI/ML Engineer to develop computer vision systems interpreting architectural drawings. The role demands expertise in Computer Vision, specifically in building and training models from classical CV methods to deep learning. Ideal candidates should have a strong mathematical foundation and at least 3 years of experience in computer vision pipelines. Applicants should send their resumes to [e-mail].

Qualifications

• 3+ years of hands-on experience building CV pipelines and production-ready ML models.
• Strong foundation in mathematics, geometry, and image processing.
• Experience with OCR (e.g., Tesseract, deep-learning-based text recognition).

Responsibilities

• Develop and optimize computer vision models for architectural drawing understanding.
• Design and train deep learning models for CAD drawing element detection.
• Collaborate with teams to integrate vision models into CAD/BIM workflows.

Skills

Computer Vision expertise

Python programming

Machine Learning frameworks (PyTorch, TensorFlow)

Education

Bachelor’s, Master’s, or PhD in Computer Science

Tools

OpenCV

Docker

Job description

AI/ML Engineer – Architectural Drawing Understanding (US)

Los Angeles, CA, USA

Responsibilities

We are seeking an AI/ML Engineer with strong expertise in Computer Vision (CV) to build intelligent systems that can interpret architectural drawings in DWG format. The role emphasizes designing and training computer vision pipelines — from classical CV methods to state-of-the-art deep learning models — to extract geometry, text, symbols, and structural information from technical drawings. While CAD format familiarity is helpful, deep CV expertise is the primary requirement.

• Develop and optimize computer vision models (classical + deep learning) for entity detection, segmentation, symbol recognition, and annotation extraction from architectural drawings.
• Apply classical CV techniques (e.g., edge detection, contour analysis, Hough transform, morphological operations) alongside deep learning models to solve vector and raster understanding tasks.
• Design and train deep learning models (e.g., CNNs, Mask R-CNN, U-Net, YOLO, DETR, Vision Transformers) for detection and segmentation of CAD drawing elements.
• Implement OCR pipelines for text and dimension extraction in drawings.
• Build robust data pipelines: preprocessing DWG files, rasterization/vectorization, augmentation, and dataset creation for supervised training.
• Benchmark, evaluate, and continuously improve model accuracy, robustness, and efficiency.
• Collaborate with cross-functional teams to integrate vision models into design automation and CAD/BIM workflows.

Qualifications

EDUCATION & BACKGROUND

• Bachelor’s, Master’s, or PhD in Computer Science, Artificial Intelligence, Computer Vision, or related fields.
• Strong foundation in mathematics, geometry, and image processing.

COMPUTER VISION EXPERTISE (PRIORITY)

• 3+ years of hands-on experience building CV pipelines and production-ready ML models.
• Proven track record with classical CV algorithms (OpenCV, scikit-image): contour/edge detection, shape matching, geometric transformations, Hough transform, morphological filtering.
• Strong experience training and deploying deep learning CV models: CNNs, U-Net, Mask R-CNN, Faster R-CNN, YOLO, DETR, Vision Transformers, SAM, etc.
• Experience with OCR (e.g., Tesseract, deep-learning-based text recognition).
• Practical experience in combining classical CV with deep learning for hybrid solutions.

TECHNICAL SKILLS

• Proficiency in Python and ML frameworks (PyTorch, TensorFlow).
• Strong engineering practices: Git, CI/CD, testing, Docker, and scalable inference deployment.
• Familiarity with vector graphics, CAD data formats (DWG/DXF), and computational geometry is a plus, but not mandatory.

PREFERRED SKILLS

• Knowledge of geometric deep learning or graph-based approaches for structured vector data.
• Experience with annotation tools, dataset creation, and augmentation for CV tasks.
• Familiarity with AEC (Architecture, Engineering, Construction) workflows is an advantage.

About Us

Established in 2023, Genia is dedicated to empowering the North American real estate market with generative AI. Our product, Structural CoPilot, automates the generation of structural engineering design drawings for the construction sector, enhancing efficiency and quality for engineering design firms and real estate developers.

The founding team has a deep background in the architecture and AI industries, with experience from leading internet and architectural engineering companies such as Amazon, Tencent, and ARUP. Team members hold degrees from renowned universities, including Yale, UPenn, Columbia, CMU, Duke, UCLA, and UBC. They have a proven track record of building multiple AI products from the ground up.

In early 2024, Genia successfully closed a multi-million dollar financing round with investors including a top-tier Silicon Valley venture capital firm and Europe\'s largest construction technology fund. We have also established strategic partnerships with several North American architectural engineering firms. The company is in a phase of rapid expansion and offers a competitive compensation package, including equity incentives for outstanding talent. We sincerely invite talented individuals from all backgrounds to join us!

Apply Now

If you are interested in joining us, send your resume and any other materials to hr [at] genia.design. We look forward to working with you soon!