Design Sculptor – Computational

Responsibilities

• Develop and apply computational design tools to meet quality and time requirements as directed by Sculpting Leadership for assigned programs.
• Streamline design processes in the creation of aesthetic models.
• Create and manage Computational Design definitions and scripts for digital models, simulations, and visualization to support decision-making throughout the design process.
• Use and create Computational Design algorithms to build complex sculpted surfaces throughout the GVDP.
• Mentor sculptors on the use, theory, and implementation of Computational Design.
• Ensure that computational design tools and processes adhere to common GM Global Design processes and best practices.
• Support surface releases which meet Design approval, production engineering, and data release requirements.
• Comprehend program timelines and all relating model quality requirements.
• Adhere to corporate data management processes including Teamcenter, SharePoint, and communication systems.

• Bachelor’s degree in Industrial Engineering, Mechanical Engineering, Information Science, or related field of study.
• Three (3) years of experience as a Lab Engineer, Augmented Reality Designer and Developer, or related occupation in Automotive Design.
• One (1) year of experience with programming including Python for developing automation logic and interactive workflows tailored to automotive design.
• Developing advanced tools and scripts automation for real-time design and extending software functionality beyond native capabilities.
• Building applications specifically for creative automotive design, ergonomic evaluation, and interactive sculpting workflows.
• Designing and deploying computational pipelines that integrate design visualization with enterprise or cloud-based systems and multi-disciplinary data.
• Incorporating human-centered ergonomic and engineering constraints into computational design and simulation processes.
• Creating immersive simulation environments that unify automotive design, human factors, and manufacturing validation.
• Data-driven design automation for interactive 3D visualization and cross-disciplinary design reviews.