Machine Learning Engineer

To solve complex spatial alignment and validation challenges, the full-time Machine Learning Engineer will work remotely to build infrastructure bridging CAD designs with real-world 3D reconstructions, focusing on automating the "Ground Truth" process and developing metrics for validating digital components in 3D environments. Key responsibilities Develop pipelines for aligning 3D meshes with CAD models using high-precision spatial transforms Build autonomous agents to manage data ingestion, scale correction, and final metric validation Architect automated systems to detect and correct data pipeline failures and integrate alignment metrics into the ML inference flow Required qualifications Proficiency in Geometric Deep Learning with tools such as Open3D, PyTorch3D, or Trimesh Experience with agentic frameworks like LangChain or AutoGPT for building autonomous workflows Expertise in orchestration tools such as Dagster or Apache Airflow for monitoring data pipelines Strong programming skills in Python and a Bachelor's/Master's degree in Computer Science, Engineering, or a related field Familiarity with deploying ML workloads on cloud platforms like AWS, GCP, or Azure using Docker and Kubernetes