• Design, develop, and deploy AI/ML models to automate and improve internal workflow and review processes • Build and maintain ML pipelines within an AWS cloud environment • Collaborate with product and engineering teams to identify high-value automation opportunities and translate them into production-ready solutions • Integrate ML capabilities into existing Java and React application workflows • Monitor model performance and iterate based on real-world outcomes and stakeholder feedback • Ensure all AI/ML implementations meet federal security and compliance requirements including FISMA and NIST 800-53

• Develop and refine the AI algorithms that automatically generate precise 3D garment geometry and textures from 2D photos. • Transform a manual process that currently takes hours into an automated one that takes minutes. • Create and optimize Deep Learning models for 2D-to-3D transformation, focusing on mesh structure and vertex topology. • Work with convolutional layers, autoencoders, transformers, and Generative Adversarial Networks (GANs). • Curate and augment datasets by blending real-world photography with synthetically generated data. • Develop software modules using Python APIs for integration into professional 3D environments like Clo3D and Marvelous Designer. • Conduct scientific experiments, define quality criteria, and document findings to reach Technology Readiness Level 9 (TRL9).

• Work with stakeholders to define machine learning solution designs based on cloud services such as Azure and Snowflake. • Design, build, and maintain machine learning pipelines and frameworks to support enterprise analytics, reporting, and product needs. • Collaborate with data science, ML engineering, data quality, and product teams on model deployment architecture and implementation. • Manage, configure, and optimize cloud environments and related machine learning services. • Implement tools and processes for model integration, storage, profiling, monitoring, processing, management, and archival. • Support enterprise-wide model governance, performance tracking, and lifecycle management standards. • Recommend improvements to ML platforms, tools, and development practices to support strategic technology and business objectives. • Work with SaaS vendors and strategic partners to implement and maintain modern machine learning solutions. • Use Agile practices to manage delivery, contribute to project planning, and support successful rollout of ML products. • Partner with internal stakeholders to understand business requirements and translate them into reliable ML operations solutions. • Stay current with emerging MLOps tools, cloud technologies, and best practices to ensure solutions remain scalable, secure, and fit for purpose.

• Construir pipelines CI/CD de agentes en Azure. • Desplegar y operar soluciones IA. • Integrar AI Foundry con entornos corporativos. • Monitorizar rendimiento y disponibilidad. • Automatizar tareas de operación.