hud

17 hours ago

Lead Research Engineer, Data Quality

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 11 hours agoStatus: Live

Job Summary

Own how HUD measures, improves, and scales the quality of training data for frontier agents. Lead a data quality team building QC systems and experiments to grade agent outputs across RL environments, synthetic data, benchmarks, and domain workflows. Develop scalable validation methods (failure-mode analysis, task mutation checks, trajectory auditing), partner with researchers and vendors to debug issues, and turn insights into production pipelines, dashboards, and feedback loops while mentoring engineers.

Location: San Francisco, Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Seniority: Mid level

Key Responsibilities

•Lead the data quality strategy by building QC systems, defining and enforcing quality standards, and designing experiments to grade agent outputs.
•Develop new 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.
•Convert qualitative research insights into production systems, internal tools, dashboards, validation pipelines, and feedback loops.
•Mentor other research engineers to maintain high standards for technical rigor, clarity, and execution speed.

Pay and Benefits

Perks:MedicalDentalVisionMeal AllowancePaid HolidaysPaid Leave401kCommuter BenefitsEquinoх Membership

Key Requirements

•Advanced proficiency in Python and Docker, working effectively in Linux environments.
•Strong 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.
•Ability to work across messy human and technical systems, including domain experts, vendors, generated data, model outputs, graders, and infrastructure.
•Strong written communication to clearly explain methodology to researchers, engineers, labs, and external audiences.

Experience:5+ yearsSynthetic dataData qualityMachine learningRL environments

Skills:Written communicationMentoringExperiment designTechnical rigorAttention to detail

Tech Stack:PythonDockerLinuxChatGPTClaude CodeCursor

Eligibility

Nationality:US National

Company Brief

hud

Hud provides a lightweight developer-focused tool that captures and shares UI components and interactive design specs from the browser to streamline design-to-development handoff and collaboration between designers and engineers.

Industry: Developer Tools

Website

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