We are looking for a Machine Learning Engineer with strong expertise in computer vision and object detection to tackle a specialized challenge : detecting walls and identifying rooms in architectural blueprints or pre-construction plans.
This role is ideal for someone who is hands-on, detail-oriented, and passionate about applying advanced ML techniques to solve real-world problems.
Key Responsibilities
- Develop and fine-tune ML models for detecting walls in architectural blueprints.
- Design and implement preprocessing pipelines for handling blueprint files (images / PDFs).
- Optimize model inference using ONNX Runtime for production-ready deployment.
- Build and maintain an API server to serve ML inference (preferably using BentoML).
- Collaborate with stakeholders to define requirements, deliver milestones, and document solutions clearly.
Must-Have Requirements
Strong hands-on experience with PyTorch for model development and training.Expertise with Ultralytics (YOLOv8) for object detection tasks.Proficiency in OpenCV, Pillow (PIL), and NumPy for preprocessing and image manipulation.Experience with ONNX / ONNX Runtime for optimized inference.Solid knowledge of BentoML (preferred) or FastAPI for serving ML APIs.Familiarity with Pydantic for schema validation.Proven track record of deploying ML models into production.Strong problem-solving mindset and ability to adapt ML tools to specialized use cases.Clear communication and documentation skills.Nice-to-Have
Experience working with PyMuPDF for parsing PDF-based architectural plans.Background in architectural / engineering data or prior work with blueprint analysis.Knowledge of clustering / grouping methods for room identification tasks.Familiarity with MLOps practices (monitoring, scaling, CI / CD for ML).Schedule : Monday to Friday - Full-time
Compensation : USD salary
Location : 100% remote
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