Senior Principal Machine Learning Engineer

Position Overview

Autodesk is hiring a Senior Principal Machine Learning Engineer for AEC Solutions to act as a technical leader and delivery owner for high-impact ML initiatives spanning foundation models, reinforcement learning, data systems, and large-scale ML platforms. The role sits at the intersection of applied research, engineering, and product, using data from AutoCAD, Revit, Autodesk Construction Cloud, and Forma to transform AEC workflows.

Responsibilities

• Define the long-term technical vision for generative AI and foundation model infrastructure within the AEC Solutions team
• Lead end-to-end delivery of complex ML systems from model architecture and data strategy through distributed training and production deployment
• Translate applied research ideas into scalable production code alongside research scientists and platform teams
• Architect distributed training workflows on large compute clusters and remove throughput bottlenecks across data and model pipelines
• Mentor senior engineers while partnering closely with product, data engineering, and platform teams on multimodal AEC data workflows

Minimum Qualifications

• Master's or PhD in Computer Science, Mathematics, Statistics, Physics, Computational Linguistics, or a related AI/ML discipline
• 10+ years of experience in machine learning, AI, or related fields with a strong track record of technical leadership and hands-on implementation
• Expert-level understanding of deep learning architectures including Transformers and diffusion models, with PyTorch required
• Hands-on experience with distributed training frameworks such as PyTorch Distributed, Ray, DeepSpeed, or Megatron in HPC or cloud environments
• Strong Python proficiency focused on production-quality code, debugging, and performance profiling
• Proven experience leading large-scale ML systems from conception to production while mentoring engineers in cross-functional environments

Preferred Qualifications

• Experience training large foundation models in distributed compute environments
• Experience building multimodal data pipelines at terabyte or petabyte scale with tooling such as Spark or Iceberg
• Experience constructing internal ML platforms with tools such as Kubernetes, Slurm, or Metaflow
• Background in AEC, computational geometry, or working with 3D data such as BIM, CAD, meshes, or point clouds

Salary range: $165,000 – $296,450 for US-based hires. The role is open across 24 eligible US locations plus remote options in Canada, and supports remote or hybrid work.