Principal​/Senior Principal Machine Learning Engineer, Generative AI

Senior/Principal Machine Learning Engineer, Generative AI

Autodesk is leading the transformation of the AEC industry, integrating AI technology into our products. We are enhancing our applications with cloud-native capabilities, including data at scale, edge computing, AI-based solutions, and advanced 3D modeling and graphics. This innovation is happening across our flagship products—AutoCAD, Revit, and Construction Cloud—and Forma, our new Industry Cloud.

Location:

Hybrid work or remote work in Canada or United States. East Coast Preferred.

• Set the strategic technical vision for Autodesk’s generative AI capabilities in the AEC domain, influencing both short-term priorities and long-term investments
• Lead the design and development of intelligent data processing and characterization systems that transform unstructured inputs (e.g., text, images, geometry) into structured, ML-ready formats
• Architect and implement scalable, production-grade data and ML pipelines that support training and fine-tuning of models
• Drive strategic technical planning across the team—identifying bottlenecks, proposing long-term architectural improvements, and aligning data/ML infrastructure with product goals
• Collaborate closely with data engineers, applied scientists, and product teams to integrate large-scale data and related attributes into model development workflows
• Perform hands-on development of data preprocessing, feature extraction, and transformation modules optimized for downstream ML model performance
• Define and establish best practices for model experimentation, evaluation, and deployment in high-throughput environments
• Investigate and apply advanced techniques including self-supervised learning, active learning, and weak supervision to maximize the value of unlabeled data
• Own and evolve the model/data feedback loop by monitoring model quality, diagnosing failure modes, and guiding iterative improvements
• Mentor and support a team of ML engineers, fostering a culture of engineering excellence, curiosity, and technical ownership
• Stay current with advances in generative AI, foundation models, and data-centric AI—translating research into practical, scalable solutions

• A Master's degree (or higher) in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics or a related field
• 10+ years of work experience in machine learning, data science, AI, or a related field with a proven track record of technical leadership and hands-on implementation
• Deep understanding of data modelling, system architectures, and processing techniques, including 2D/3D geometric data representations
• Expertise in deep learning architectures (e.g., Transformers, CNNs, GANs) and modern ML frameworks (e.g., PyTorch, Lightning, Ray)
• Experience with Large Models (LLMs and/or VLMs) and related technologies, including frameworks, embedding models, vector databases, and Retrieval-Augmented Generation (RAG) systems, in production settings
• Experience with AWS cloud services and Sage Maker Studio for scalable data processing and model development
• Strong foundation in computer science fundamentals, distributed computing, and algorithmic efficiency
• Proven ability to translate theoretical concepts into practical solutions and prototype implementations
• Ability to work autonomously while effectively collaborating across teams, bridging the gap between research and practical implementation
• Excellent technical writing and communication skills for documentation, presentations, and influencing cross-functional teams

• Background in Architecture, Engineering, or Construction
• Extensive experience in system design for data preparation, hyperparameter selection, acceleration techniques, and optimization methods
• Proficiency in parallel and distributed computing techniques, with hands-on experience using platforms like Spark, Ray, or similar distributed systems for large-scale data processing and model training
• Familiarity with responsible AI principles, including bias mitigation, explainability, and ethical AI practices

• Is passionate about solving problems for AEC customers (Architecture,…