Senior Principal Engineer in Machine Learning for Foundational Models

Job Requisition ID

26WD94805

Senior Principal Engineer in Machine Learning for Foundational Models

Position Overview

Join Autodesk as we revolutionize the Architecture, Engineering, and Construction (AEC) industry by implementing cutting-edge AI and foundational models within our cloud-native platforms, including AutoCAD, Revit, Construction Cloud, and Forma. We're seeking a Senior Principal Machine Learning Engineer to lead and execute high-impact ML projects that bridge research and engineering, driving substantial advancements in our product offerings.

Your role will be pivotal in defining technical strategies for Generative AI and Foundation Model systems within our AEC Solutions team. You'll guide the end-to-end development of complex machine learning systems, oversee the strategic architectural decisions, and mentor aspiring engineers while maintaining hands‑on involvement in challenging projects.

Responsibilities

• Technical Strategy & Leadership: Develop a long-term vision for generative AI and foundation model infrastructure. Your influence will guide architectural choices across teams.
• End-to-End Delivery: Spearhead the design and implementation of sophisticated ML systems, managing everything from model architecture and data strategy to training and deployments.
• Foundation Model Engineering: Lead the creation of advanced training pipelines, collaborating with Research Scientists to bring innovative ideas into scalable solutions.
• Scalability & Infrastructure: Build systems for distributed training on extensive computing clusters, addressing data processing bottlenecks to maximize efficiency.
• Mentorship & Influence: Coach senior engineers and nurture a culture of technical ownership while being a collaborative partner to Product Management and Engineering teams.
• Cross-Functional Collaboration: Work closely with Data Engineering, Platform, and Research teams to incorporate large-scale multimodal AEC data into our development workflows.
• Operational Excellence: Set high standards for model evaluation, versioning, and MLOps practices to ensure reliable and reproducible performance in production settings.

Minimum Qualifications

• Master's or PhD in AI/ML‑related fields like Computer Science, Mathematics, or Computational Linguistics.
• 10+ years of experience in machine learning, AI, with proven technical leadership and implementation skills.
• Experience mentoring engineers and managing technical projects in collaborative environments.
• History of delivering large‑scale ML systems from conception to deployment.
• Expertise in deep learning architectures (e.g., Transformers, Diffusion models) and modern frameworks (required: PyTorch).
• Hands‑on experience with distributed training techniques in cloud environments.
• Strong proficiency in Python, focusing on developing robust and maintainable production code.
• Excellent communication skills, translating complex concepts into actionable insights for diverse stakeholders.

Preferred Qualifications

• Experience in training large foundation models on distributed systems.
• Expertise in designing data pipelines for multimodal datasets at scale.
• Experience with ML developer platforms utilizing tools like Kubernetes or Slurm.
• A portfolio showcasing the practical application of academic research into product features.
• Background in AEC, computational geometry, or 3D data representation.

The Ideal Candidate

• Takes ownership of outcomes beyond just components.
• Has experience with operational complexities of ML systems at scale.
• Possesses strong judgment shaped through real‑world experience.
• Thrives in challenging problem spaces and drives clarity.
• Enjoys mentoring and influencing technical culture.
• Is passionate about impactful work on a large scale.

---

Autodesk celebrates a diverse and inclusive workplace, providing equal opportunities without regard to any legally protected characteristics. We also consider all qualified applicants regardless of criminal histories, consistent with applicable law.