• Lead execution of the ML roadmap, with a focus on building scalable, production-grade ML Platform infrastructure for 3D deep learning and computer vision applications. • Build and lead a high-performing ML Platform team, with an emphasis on reliability, reproducibility, and efficient model lifecycle management. • Partner with product, engineering, and research stakeholders to translate ML innovations into robust, deployable systems that support key business objectives. • Oversee the end-to-end deployment of computer vision models that extract structure from complex 3D scan data, ensuring production readiness and performance at scale. • Drive experimentation and implementation of SOTA techniques for 3D generative AI, while ensuring they are integrated into robust ML Platform workflows. • Collaborate cross-functionally to identify pain points and bottlenecks in current ML pipelines and deliver improvements through automation and tooling. • Manage large-scale data pipelines, versioning, and labeling workflows to support both generalized and fine-tuned model development. • Define and implement rigorous evaluation and monitoring strategies to maintain high model quality, mitigate drift, and ensure reliability in production. • Establish and maintain best practices for CI/CD of ML models, including model versioning, rollback mechanisms, and monitoring for performance and integrity.