Think Gen-AI for blueprints. At DraftAid, we are building software that generates CAD manufacturing drawings.
Mechanical engineers and designers spend 40% of their time creating production drawings from their 3D models. It's a tedious process, error-prone, and often delays projects by weeks! DraftAid auto-generates these detailed drawings with a single click. Engineers designing anything from skyscrapers to car parts use DraftAid to speed up their workflow. With DraftAid, designers can model, and leave the drawings to AI!
We are hiring a senior ML engineer who’s excited to bring AI into the mechanical design space.
Responsibilities
Develop and implement novel self-supervised learning approaches and prediction targets for 3D CAD data representation
Build end-to-end ML pipelines from data ingestion to production deployment
Work closely with software engineers to integrate ML models into our production systems
Continuously evaluate and optimize model performance against real-world engineering requirements
Stay current with the latest research and techniques in the field, adapting them to our unique challenges
Requirements
5+ years of experience in applied machine learning with a proven track record of shipping ML systems to production
Demonstrated expertise in developing embedding techniques and self-supervised learning approaches using transformers and diffusion models
Strong programming skills in Python and familiarity with ML frameworks such as PyTorch or TensorFlow
Experience with MLOps practices and tools for model deployment, monitoring, and management
Experience in fast-paced startup environments where pragmatic solutions take priority over academic perfection
Bachelor's degree in Computer Science, Machine Learning, or related field; advanced degree preferred
Preferred Qualifications
Experience applying ML techniques to 3D data, geometric shapes, or CAD models
Knowledge of computational geometry and its intersection with modern deep learning techniques
Experience with vector databases and similarity search infrastructure
Published research or contributions to the field of representation learning or geometric deep learning
Understanding of CAD systems, engineering workflows, or manufacturing processes
What We Offer
The opportunity to shape foundational technology and be a part of a groundbreaking startup from its early stages
A dynamic and supportive team environment where your contributions are valued and celebrated
Competitive salary and equity package
Flexible working hours
The chance to work on challenging projects that have the potential to transform manufacturing
The satisfaction of seeing your ML innovations directly impact and improve real-world engineering workflows