Teams at hud

Research Engineers will build QA systems for training data, define quality standards, audit datasets, and collaborate with data vendors to enhance data generation processes.

Lead HUD's data quality strategy for RL training data: build QC systems, validate synthetic data at scale, design evaluation experiments, partner with researchers and vendors, convert research insights into production validation pipelines and tools, and mentor research engineers.

Build and optimize HUD's comprehensive evaluation framework for Computer Use Agents (CUAs) at scale, ensuring high performance and reliability.