Latest ML Engineering jobs at hud

Lead the data quality team at HUDHUD to build QC systems, validation methods, and experiments that measure and improve training data for frontier AI agents and RL environments. Requires deep data quality intuition, Python/Docker/Linux proficiency, and experience turning research insights into production evaluation pipelines.

Build synthetic data pipelines and tasks to train frontier AI agents. Requires Python, Docker, Linux, and experience creating realistic, scalable synthetic training data for models and evals.

Build QC automation systems for RL training data and agent evals at HUDHUD. Design quality standards, validation pipelines, experiments and metrics without heavy LLM reliance; partner with vendors to debug and improve data generation. Requires Python, Docker, Linux and experience building scalable QA/QC systems end-to-end.

Applied Research Engineer owning technical deployment requests, troubleshooting, building tools/pipelines, and resolving ambiguous problems for frontier AI labs and data vendors at HUDHUD. Requires strong Python/Docker/Linux skills, eval/benchmark experience, independent problem-solving in fast-paced ambiguous settings.

Builds QA systems, tooling, and workflows to audit and validate large-scale RL training data from suppliers. Partners with vendors to improve data quality using Python, Docker, and AI/ML techniques for frontier AI infrastructure.