• Lead the design of shared platform services for agentic workflows • Define and evolve APIs, SDKs, and internal tooling for platform adoption • Design platform-level infrastructure for handling memory and context • Build and improve observability, tracing, and evaluation systems • Help design guardrails, validation layers, and policy enforcement mechanisms

• Design, construct, and manage robust data pipelines for the training, validation, and continuous retraining of Large Quantitative Models (LQMs) and agentic frameworks. • Develop, implement, and rigorously test novel ML models and algorithms, defining appropriate metrics to ensure model performance aligns with high-level product objectives. • Contribute to the efforts in cleaning, transforming, and engineering features from complex and large-scale datasets to optimize LQM performance and predictive accuracy. • Conduct deep analysis of model behavior, performance, and failure modes, tuning hyper-parameters and optimizing model architecture for efficiency, speed, and accuracy in a production context. • Collaborate closely with AI researchers, product managers, and SWEs to translate high-level business objectives into actionable ML development and deployment roadmaps. • Champion and enforce exceptional engineering standards for code quality, system efficiency, and security in a prototyping environment.

• 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).