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About the role
As a Senior Principal Machine Learning Engineer at Autodesk, you will play a crucial role in revolutionizing the Architecture, Engineering, and Construction (AEC) industry by integrating advanced AI and foundation models into cloud-native platforms like AutoCAD, Revit, Construction Cloud, and Forma. Your expertise will be instrumental in leading complex and high-impact ML initiatives, covering foundation models, reinforcement learning, data systems, and large-scale ML platforms. You will be responsible for setting technical direction while actively engaging in the most challenging and critical areas. Key Responsibilities: - Technical Strategy & Leadership: Define the long-term technical vision for Generative AI and Foundation Model infrastructure within the AEC Solutions team. Influence architectural decisions across the organization. - End-to-End Delivery: Lead the design, development, and delivery of complex ML systems. Manage the full lifecycle from model architecture selection to production deployment. - Foundation Model Engineering: Drive the development of large-scale training pipelines and collaborate with Research Scientists to implement experimental ideas efficiently. - Scalability & Infrastructure: Architect solutions for distributed training on massive compute clusters, resolving bottlenecks to maximize training throughput. - Mentorship & Influence: Mentor engineers, foster technical ownership, and partner with Product Management and Engineering leadership. - Cross-Functional Collaboration: Collaborate with Data Engineering, Platform, and Research teams to integrate large-scale multimodal AEC data into model development workflows. - Operational Excellence: Establish standards for model evaluation, monitoring, and MLOps best practices to ensure reproducibility and reliability in a production environment. Qualifications Required: - Masters or PhD in a field related to AI/ML. - 10+ years of experience in machine learning or related fields. - Demonstrated leadership in technical projects and mentoring engineers. - Expert-level understanding of deep learning architectures and modern frameworks. - Hands-on experience with distributed training frameworks and techniques. - Strong proficiency in Python and ability to translate complex technical concepts effectively. The Ideal Candidate for this role is someone who owns outcomes, operates ML systems at scale, demonstrates strong technical judgment, thrives in ambiguous problem spaces, enjoys mentoring, and is motivated by delivering real-world impact. Please note that Autodesk is committed to building a diverse and inclusive workplace, where all qualified applicants are considered for employment based on their skills and experience, regardless of race, color, religion, gender, sexual orientation, or any other legally protected characteristic. As a Senior Principal Machine Learning Engineer at Autodesk, you will play a crucial role in revolutionizing the Architecture, Engineering, and Construction (AEC) industry by integrating advanced AI and foundation models into cloud-native platforms like AutoCAD, Revit, Construction Cloud, and Forma. Your expertise will be instrumental in leading complex and high-impact ML initiatives, covering foundation models, reinforcement learning, data systems, and large-scale ML platforms. You will be responsible for setting technical direction while actively engaging in the most challenging and critical areas. Key Responsibilities: - Technical Strategy & Leadership: Define the long-term technical vision for Generative AI and Foundation Model infrastructure within the AEC Solutions team. Influence architectural decisions across the organization. - End-to-End Delivery: Lead the design, development, and delivery of complex ML systems. Manage the full lifecycle from model architecture selection to production deployment. - Foundation Model Engineering: Drive the development of large-scale training pipelines and collaborate with Research Scientists to implement experimental ideas efficiently. - Scalability & Infrastructure: Architect solutions for distributed training on massive compute clusters, resolving bottlenecks to maximize training throughput. - Mentorship & Influence: Mentor engineers, foster technical ownership, and partner with Product Management and Engineering leadership. - Cross-Functional Collaboration: Collaborate with Data Engineering, Platform, and Research teams to integrate large-scale multimodal AEC data into model development workflows. - Operational Excellence: Establish standards for model evaluation, monitoring, and MLOps best practices to ensure reproducibility and reliability in a production environment. Qualifications Required: - Masters or PhD in a field related to AI/ML. - 10+ years of experience in machine learning or related fields. - Demonstrated leadership in technical projects and mentoring engineers. - Expert-level under