Research Engineer - Quality Assurance for Training Data

hud • United States

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AI Summary

We're looking for research engineers to help build out QA for training data created by companies using HUD's infrastructure. You'll define and enforce quality standards, build tooling and workflows, and partner with data vendors. Proficiency in Python, Docker, and Linux environments is required.

Key Highlights

Define and enforce quality standards for training data

Build tooling and workflows for auditing supplier-generated datasets

Partner with data vendors to debug quality issues

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Key Responsibilities

Define and enforce quality standards for training data

Build tooling and workflows to audit supplier-generated datasets

Determine if and how human-in-the-loop review workflows can be used to optimize QA

Partner with data vendors to debug quality issues

Technical Skills Required

Python Docker Linux

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Benefits & Perks

Competitive compensation

100% covered top-of-the-line medical, dental, and vision

Relocation assistance

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Nice to Have

Experience building data validation pipelines and/or human-in-the-loop review systems

Familiarity with current AI tools and LLM capabilities

Job Description

HUD is building infrastructure to create RL training data and evals for frontier AI agents, as well as a marketplace to sell these to frontier labs through the HUD marketplace. Our platform is used by frontier labs, Fortune 500 companies, and startups. We’ve raised $15M from top VCs and were YC W25.We're looking for to help build out QA for training data created by companies using HUD’s infrastructure. You’ll build the systems that scale quality to help us meet our continued strong demand.

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