Related skills
r sql quality assurance python machine learning📋 Description
- Set global quality strategy across annotation, feedback, model eval, multilingual data.
- Define and enforce quality standards, acceptance criteria, and playbooks.
- Own the quality measurement system: sampling, metrics, drift detection.
- Lead a globally distributed quality organisation with asynchronous rhythms.
- Embed quality from kickoff to delivery; audits and root-cause analysis.
- Partner with Product/Engineering/Operations to embed quality in tooling.
🎯 Requirements
- 8–12+ years in quality, data ops, trust, or ML eval; 3+ years leading teams.
- Proven experience running quality programs across globally distributed teams.
- Strong statistical intuition (sampling, agreement, bias/variance) with quality data.
- SQL and dashboards; Python or R for analysis or automation.
- Deep understanding of human-in-the-loop systems and data quality impact.
- Ability to balance speed, cost, and quality; explicit trade-offs.
- Clear, confident communication with engineers and executives.
- Multilingual or localisation QA experience.
🎁 Benefits
- Competitive salary and benefits.
- Remote working within a mission-driven culture.
- Base salary, equity, and benefits; potential cash bonus.
- Salary range shown; recruiter shares specifics.
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