Lead Research Engineer, Data Quality

Job not on LinkedIn

🔥 1 minute ago

🌐 United States, Singapore – Remote

🇺🇸 United States – Remote 🇸🇬 Singapore – Remote

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 15%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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hud (YC W25)

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2025

🤖 Artificial Intelligence

☁️ SaaS

🤝 B2B

Artificial Intelligence • SaaS • B2B

hud is an evaluation platform designed for AI agents, facilitating the assessment and iteration of these agents across a variety of environments and tasks. With tools that cater to both researchers and professionals, hud allows users to rapidly evaluate their AI models and integrate existing tools while ensuring swift results through the orchestration of concurrent machine evaluations. Its flexible architecture supports customized tasks and diverse workflows, making it a robust solution for enhancing AI performance and capabilities.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

• 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