Principal Machine Learning Engineer, 3D Data, Generative AI Systems

Job Description: • Set the technical vision for 3D data retrieval and representation learning across Autodesk’s AEC AI initiatives • Influence short- and long-term investments in models, data infrastructure, and ML systems • Identify architectural gaps and scalability bottlenecks, and drive cross-team alignment on long-term solutions • Design and implement new ML models for 3D data understanding and retrieval, including geometric embeddings and multimodal representations • Apply advanced techniques such as self-supervised learning, weak supervision, and active learning to leverage large volumes of unlabeled design data • Optimize data representations and feature extraction pipelines for downstream model performance and retrieval quality • Architect and own production-grade ML pipelines, orchestrated with Airflow, supporting large-scale data preprocessing, model training and fine-tuning, evaluation and deployment workflows • Build scalable systems on AWS, including integration with SageMaker and distributed training or data processing frameworks • Establish best practices for model experimentation, versioning, evaluation, and monitoring in high-throughput environments • Lead the development of intelligent data processing systems that transform unstructured 3D, text, and image data into ML-ready formats • Own the model/data feedback loop, monitoring quality, diagnosing failure modes, and guiding iterative improvements based on real-world usage • Collaborate with data engineers and applied scientists to ensure data quality, lineage, and reproducibility • Work closely with AI researchers, software architects, and product teams to integrate models into customer-facing workflows • Mentor and guide ML engineers, raising the technical bar and fostering a culture of ownership, rigor, and curiosity • Communicate complex technical ideas clearly through documentation, design reviews, and cross-functional presentations Requirements: • Master’s degree or higher in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics, or a related field • 10+ years of experience in machine learning or AI, with demonstrated technical leadership and hands-on model development • Strong expertise in deep learning architectures (e.g., Transformers, CNNs, GANs) and modern ML frameworks such as PyTorch, Lightning, and Ray • Proven experience building new models (not just applying existing ones), especially for retrieval, embeddings, or representation learning • Deep understanding of 3D data representations and processing techniques (e.g., meshes, point clouds, CAD/BIM geometry) • Experience building and operating production ML pipelines, including orchestration with Airflow • Hands-on experience with AWS and SageMaker for scalable training and deployment • Strong foundations in computer science, distributed systems, and algorithmic efficiency • Excellent written and verbal communication skills, with the ability to influence across teams. Benefits: • Health insurance • Retirement plans • Paid time off • Flexible work arrangements • Professional development opportunities Apply tot his job