AI/ML Engineer – Architectural Modeling (Intern) - US

About the Role

Assist in developing and testing computer vision models for detecting and segmenting elements in architectural drawings, with the opportunity for a full-time offer for outstanding performers. Gain front-line, practical experience at a star startup where your work will be rapidly integrated into product prototypes and used by real users.

Responsibilities

• Assist in developing and testing computer vision models for detecting and segmenting elements in architectural drawings.
• Apply and experiment with classic CV techniques (e.g., edge detection, contour analysis, shape recognition) on drawing data.
• Train and evaluate deep learning models (e.g., CNN, U-Net, YOLO, Mask R-CNN) under the guidance of senior engineers.
• Support the data preparation pipeline, including DWG preprocessing, rasterization, augmentation, and dataset annotation.
• Document experimental processes, benchmark results, and share insights with the team.
• Collaborate with engineers and researchers to integrate models into our Structural AI Agent.

Education & Background

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Computer Vision, or a related field (preference for students from top-tier universities).
• Experience from courses, internships, or projects in computer vision, image processing, or machine learning is preferred.

Computer Vision Skills

• Familiar with classic CV algorithms (e.g., contour/edge detection, shape analysis, geometric transformations), preferably with OpenCV.
• Experience building, training, and evaluating deep learning CV models (e.g., CNN, U-Net, YOLO, Mask R-CNN, ViT).
• Knowledge of OCR and text recognition methods is a plus.

Technical Skills

• Proficient in Python and at least one ML/CV framework (e.g., PyTorch, TensorFlow, OpenCV).
• Experience with Jupyter Notebook, Git, NumPy, Pandas, and Shapely.
• Familiarity with CAD formats (DWG, DXF) or computational geometry is a plus (not required).

Soft Skills

• Enthusiastic about the startup environment; able to adapt to a fast pace and uncertainty.
• Eager to learn, willing to experiment, and possess strong problem-solving skills.
• A good communicator, able to share results and challenges with the team.