Research Engineer, Agentic AI Evals

Proficiency in Python, Docker, and Linux environments React experience for frontend development Production-level software development experience preferred Strong technical aptitude and demonstrated problem-solving ability Startup experience in early-stage technology companies with ability to work independently in fast-paced environments Strong communication skills for remote collaboration across time zones Familiarity with current AI tools and LLM capabilities Understanding of safety and alignment considerations in AI systems Evidence of rapid learning and adaptability in technical environments Hands-on experience with or contributed to LLM evaluation frameworks (EleutherAI, Inspect, or similar) Built custom evaluation pipelines or datasets Worked with agentic or multimodal AI evaluation systems

Build out environments for HUD's CUA evaluation datasets, including evals for safety redteaming, general business tasks, long-horizon agentic tasks etc. Deliver custom CUA datasets and evaluation pipelines requested by clients Contribute to improving the HUD evaluation harness