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Tell HUD's story and evangelize vision; source and meet candidates, AI engineers, and ecosystem partners; define culture, screen and onboard hires; build recruiting ops and tooling; run events and content; collaborate with marketing, Chief of Staff, and GTM engineers to drive introductions and community growth.

Build scalable QC systems and validation pipelines for RL training data: define quality standards, design metrics and experiments, audit supplier datasets, partner with vendors to diagnose failures, and integrate learnings into infrastructure and vendor tooling.

Design, implement, and maintain domain-specific benchmarks and infrastructure to run agents/models. Define tasks with subject experts, develop metrics and analyses, validate benchmark relevance to real-world evals, and produce clear technical documentation and reports.

The recruiter will manage end-to-end recruiting for technical and go-to-market roles, optimizing processes and collaborating with team leads while sourcing top candidates and supporting new hire onboarding.

The GTM Engineer is responsible for managing HUD's outbound sales pipeline, optimizing conversion metrics, and developing GTM workflows, targeting technical buyers. The role requires technical aptitude and sales skills relevant to AI and ML domains.

Lead implementation and deployments for frontier AI labs and data vendors: triage technical requests, build tools and one-off pipelines, diagnose ambiguous problems across code/data/environments, coordinate cross-functionally, and turn recurring manual work into reusable processes.

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

The Marketing & Events Lead will develop and implement marketing strategies, grow social media presence, manage events, and effectively communicate HUD's mission and product narrative.