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Research Engineer, QC Automation

hud
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Hybrid (San Francisco), Hybrid (Singapore)$135k - $230kFull-timePosted 3mo ago

About the role

HUD is building a platform and marketplace for AI data. This role focuses on automating QC for training data to scale quality and meet demand.

Responsibilities

  • Create QC systems based on true understanding and human judgement, without relying heavily on LLMs
  • Define and enforce quality standards for training data
  • Design experiments and metrics to grade agent outputs
  • Partner with data vendors to debug quality issues and diagnose agent failure modes, provide actionable feedback, and improve their data generation processes
  • Translate QC learnings into systems for auditing supplier-generated datasets, including sampling strategies, validation pipelines (rule-based and model-assisted), and feedback loops
  • Continuously integrate QC learnings into infrastructure tools and data vendor portal to reduce anomalies, inconsistencies, and edge cases

Qualifications

  • Proficiency in Python, Docker, and Linux environments
  • Strong understanding of what “good data” means and how to measure it
  • Genuine curiosity of different domains and great at asking questions to understand them
  • Built scalable data validation pipelines and automated QA/QC systems end-to-end without a fully prescribed roadmap
  • Experience working on benchmarks and evals - you can reason about task realism, rubrics, environments, and RL training trajectories
  • Early-stage startup experience with ability to work independently in fast-paced environments

Skills

Required:PythonDockerLinuxQuality Control / QA for dataExperiment design and metricsData validation pipelines
Nice to have:Benchmarks and evals for RLCommunication across time zones

Benefits

  • Competitive compensation
  • 100% covered top-of-the-line medical, dental, and vision (US and Singapore employees)
  • Lunch and dinner for in-office employees
  • Company-wide holiday break (Christmas Eve to New Year’s Day) on top of PTO and paid holidays
  • Equinox membership, 401k, and commuter benefits (US employees) and health/wellness stipend (Singapore employees)
  • Unlimited access to tokens for ChatGPT, Claude Code, Cursor, etc. (no practical limit observed)
  • Annual travel budget to visit either office
Last updated Oct 21, 2026. Interested? Apply on the company site.
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About hud

Platform for building RL environments and evals

HUD (YC W25) is developing agentic evals and RL environments for Computer Use Agents (CUAs) that browse the web for frontier AI labs. Our CUA Evals framework is the first comprehensive evaluation tool for CUAs. People don't actually know if AI agents are working reliably. To make AI agents work in the real world, we need detailed evals for a huge range of tasks. We're backed by Y Combinator, and work closely with frontier AI labs to provide agent evaluation and training infrastructure at scale.

artificial-intelligencereinforcement-learning
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