Research Engineer for Quality Assurance

hud • United States

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AI Summary

We're looking for a research engineer to help build out QA for training data created by companies using HUD's infrastructure. The role involves defining quality standards, building tooling and workflows, and partnering with data vendors. The ideal candidate has proficiency in Python, Docker, and Linux environments, and experience with large-scale datasets.

Key Highlights

Define and enforce quality standards for training data

Build tooling and workflows to audit 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

Partner with data vendors to debug quality issues

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

Continuously integrate QA learnings into infrastructure tools and data vendor portal

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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