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Lead Research Engineer, Data Quality
Summary by AIEngineer.careers
Lead Research Engineer, Data Quality is a AI Data Engineer role (full-time). with Clera. in SAN FRANCISCO, US. Compensation shown: $150K–$180K. Imported listing (source: kairos.dhiti.dev). Apply on the employer's site (kairos.dhiti.dev).
Imported listing (source: kairos.dhiti.dev) · Apply on kairos.dhiti.dev
SAN FRANCISCO · US
$150K–$180K
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from kairos.dhiti.dev
Clera is seeking a Lead Research Engineer to define and scale data quality strategies for frontier AI agents. This role sits at the intersection of research and engineering, focusing on building evaluation systems, synthetic data validation, and QC pipelines that ensure high-quality training data. You will lead a team in developing metrics and tools to grade agent outputs and improve data generation workflows.
Responsibilities
- Lead the data quality team in building evaluation systems across RL environments and synthetic data.
- Define data quality strategy by building QC systems and enforcing standards for agent outputs.
- Develop methods for validating synthetic data at scale, including failure-mode analysis and trajectory auditing.
- Translate qualitative research insights into production systems like validation pipelines and dashboards.
- Mentor research engineers to maintain high technical rigor and execution speed.
Requirements
- 5+ years of experience in research or data quality engineering for AI/ML data evaluation.
- Demonstrated experience leading technical projects or teams in ambiguous, open-ended problems.
- Advanced proficiency in Python, Docker, and Linux environments.
Clera
San Francisco · US · 15+ employees
Clera is an AI-powered talent agent that connects professionals with roles at venture-backed startups. It aims to streamline the job search process by matching candidates based on their skills and goals for direct introductions to hiring managers.
