About HUD

HUD's mission is to build reliable, fair and open infrastructure for AI data. We want data to be valuable for the people who create it and trustworthy for the labs that train on it. Our team is a quickly growing group of researchers, engineers and operators building the economy that shapes what AI will become. Backed by $16M from top VCs and YC (W25), our marketplace and platform are used by startups, Fortune 500 companies and frontier labs.

About the role

We’re looking for a Research Manager to lead research that makes HUD’s agent training data and evals more useful for improving frontier models. You’ll lead research engineers through ambiguous projects, and turn findings into methods that can be used at scale.

You’ll stay close to the technical work while helping the team choose the right questions, run rigorous experiments, and deliver results. This role calls for an understanding of how and why models train: which signals teach useful behavior, where apparent progress is misleading, and how data and eval design can change outcomes.

Responsibilities

• Set the research direction for data quality, including how HUD measures how training data impacts agent behavior and performance after training, and what makes data valuable

• Lead synthetic data efforts to understand how various data types can be efficiently transformed into formats useful for training

• Lead research engineers from problem definition through experiments, implementation, and clear conclusions; coach them to strengthen technical judgment and execution

• Design and review experiments that connect model behavior and failure modes to data, environment, and reward design

• Develop methods for validating and improving training data at scale, including trajectory audits, adversarial checks, and feedback loops that help users improve their data

• Partner with research engineers, domain experts, and data vendors to turn research insights into better workflows, tools, and quality standards

• Communicate findings and tradeoffs clearly so the team can prioritize work and apply what it learns across research areas

Experience

You may be a good fit if you have:

• Experience leading technical research projects to completion, from an open question to evidence, a decision, and a working result

• Experience directly managing and mentoring researchers or research engineers while remaining engaged in technical work