Lead Machine Learning Engineer

Position Overview

Join us as we revolutionize the Architecture, Engineering, and Construction (AEC) industry by integrating advanced AI and foundation models into our cloud-native platforms like AutoCAD, Revit, Construction Cloud, and Forma. In the role of Lead Machine Learning Engineer, you will serve as a technical leader and delivery owner for impactful ML projects that span foundation models, reinforcement learning, data systems, and large-scale ML platforms. This role combines applied research, engineering, and product collaboration, allowing you to set technical direction while remaining hands-on in solving high-complexity challenges.

Key Responsibilities

• Technical Strategy & Leadership: Develop the long-term vision for Generative AI and Foundation Model infrastructure, influencing architectural decisions throughout the organization.
• End-to-End Delivery: Lead the design, development, and deployment of intricate ML systems, managing the entire lifecycle from model architecture selection to production deployment.
• Foundation Model Engineering: Spearhead the creation of extensive training pipelines, collaborating with Research Scientists to transform experimental ideas into effective and scalable code.
• Scalability & Infrastructure: Design solutions for distributed training on large compute clusters while resolving bottlenecks to maximize training throughput.
• Mentorship & Influence: Guide Principal and Senior engineers, promoting technical ownership, rigorous experimentation, and best practices.
• Cross Functional Collaboration: Work seamlessly with Data Engineering, Platform, and Research teams to integrate large-scale multimodal AEC data (3D geometry, images, text) into model development workflows.
• Operational Excellence: Set standards for model evaluation, versioning, monitoring, and MLOps best practices to ensure reliability and reproducibility.

Minimum Qualifications

• Master's or PhD in AI/ML, Computer Science, Mathematics, or related fields.
• 10+ years of experience in machine learning and AI with a strong background in technical leadership.
• A proven record of mentoring engineers and leading technical projects in cross-functional teams.
• Expert understanding of deep learning architectures and modern frameworks (PyTorch required).
• Hands-on experience with distributed training frameworks and cloud environments (AWS/Azure).
• Strong proficiency in Python, focusing on performance profiling and maintainable production code.

Preferred Qualifications

• Experience with large foundation model training in distributed environments.
• Expertise in designing data pipelines for multimodal datasets at terabyte/petabyte scale.
• Familiarity with internal developer platforms for ML using tools like Kubernetes or Slurm.
• A portfolio showcasing successful translations of academic research into product features.
• Background in AEC or experience with 3D data representations.

The Ideal Candidate

You will be someone who:

• Owns outcomes beyond components.
• Has experience operating ML systems at scale.
• Brings strong technical judgement shaped by practical experience.
• Thrives in solving ambiguous problems and driving clarity.
• Enjoys mentoring and shaping technical culture.
• Is motivated by delivering significant real-world impact.

Benefits

We provide a comprehensive benefits package that prioritizes your health and wellness, including time off, health and financial support to help you do your best work.

Equal Employment Opportunity

We are committed to building a diverse and inclusive culture, welcoming candidates from all backgrounds.

Diversity & Belonging

We are proud to cultivate a community where everyone can succeed.