Lead Research Engineer, Data Quality

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🕒 Setembro 23

🌐 Estados Unidos, Singapura – Remoto

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🏄 California – Remoto

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⏰ Tempo Integral

🟠 Sênior

🚰 Engenheiro de Dados

👻 Score fantasma 15%

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🗣️🇺🇸🇬🇧 Inglês obrigatório

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Logo of hud (YC W25)

hud (YC W25)

1 - 10 funcionários

Fundada em 2025

🤖 Inteligência Artificial

☁️ SaaS

🤝 B2B

Artificial Intelligence • SaaS • B2B

A hud é uma plataforma de avaliação desenvolvida para agentes de IA, que facilita a avaliação e a iteração desses agentes em diversos ambientes e tarefas. Com ferramentas voltadas tanto para pesquisadores quanto para profissionais, a hud permite avaliar rapidamente modelos de IA e integrar ferramentas existentes, garantindo resultados ágeis por meio da orquestração de avaliações simultâneas em máquinas. Sua arquitetura flexível oferece suporte a tarefas personalizadas e fluxos de trabalho diversos, tornando-a uma solução robusta para aprimorar o desempenho e as capacidades da IA.

Descrição

• Lead HUD’s data quality strategy, including building QC systems, defining and enforcing quality standards, and designing experiments to grade agent outputs • Develop methods for validating synthetic data at scale, including failure-mode analysis, task mutation checks, and trajectory auditing • Partner with research engineers, domain experts, and data vendors to diagnose quality issues and improve data generation workflows • Turn qualitative research insights into production systems, internal tools, dashboards, validation pipelines, and feedback loops • Build internal research taste around what makes agent training data useful, not just superficially correct • Mentor research engineers to maintain high standards for technical rigor, clarity, and execution speed • Lead the data quality team in evaluating thousands of tasks across RL environments, synthetic data, benchmarks, and domain-specific workflows

🎯 Requisitos

• Advanced proficiency in Python, Docker, and Linux environments • Deep intuition for data quality, including what makes tasks realistic, learnable, diverse, reliable, and useful for training • Experience building QC systems, evals, benchmarks, synthetic data pipelines, validation workflows, or model evaluation infrastructure • Comfort working across messy human and technical systems, including domain experts, vendors, generated data, model outputs, graders, and infrastructure • Strong written communication and ability to explain methodology clearly to researchers, engineers, labs, and external audiences • Experience leading teams on ambiguous technical projects from problem definition through implementation and iteration • Experience working with subject-matter experts to capture domain judgment and convert it into scalable review or generation systems • Ability to design metrics, experiments, and QA/QC processes • Early-stage startup experience and ability to work independently in fast-paced environments • Detail-oriented with ability to spot subtle inconsistencies or edge cases in data • Ability to work hours that overlap 70–80% with San Francisco or Singapore time zones

🏖️ Benefícios

• 100% covered top-of-the-line medical, dental, and vision from Blue Shield of CA (US employees) • Lunch and dinner when you’re in the office (in-office employees) • Company-wide holiday break (Christmas Eve to New Year’s Day) on top of PTO and paid holidays • Equinox membership (US employees) • 401k (US employees) • Commuter benefits (US employees) • Unlimited access to tokens for ChatGPT, Claude Code, Cursor, etc. • Support for relocation and visas for strong full-time candidates to the US or Singapore

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