Lead Research Engineer, Data Quality (Visa Sponsorship - United States)

Visa sponsorship available. An early-stage AI company is hiring a leader for its data quality team. The company builds infrastructure for reinforcement learning and model evaluation, and the role focuses on how training data is assessed and improved so that research teams can build more reliable AI agents. You will set the direction for quality standards and turn research findings into production tooling.

What you'll do

• Lead the development of systems that evaluate tasks across reinforcement learning environments, synthetic data, benchmarks and domain-specific workflows.
• Define data quality strategy, set standards and design experiments to measure agent outputs.
• Build scalable methods to validate synthetic data, including failure analysis, task mutation checks and trajectory audits.
• Partner with research engineers, domain experts and data vendors to diagnose quality issues and improve data generation.
• Convert research insights into production tools, dashboards, validation pipelines and feedback loops.
• Mentor research engineers and encourage technical rigor, clear communication and strong execution.

What you need

• At least 5 years of research or engineering experience in AI/ML data evaluation or data quality systems.
• Prior experience leading technical projects or teams through ambiguous problems from definition through iteration.
• Advanced proficiency in Python, Docker and Linux.
• Background in AI evaluations, post-training, benchmarks, synthetic data pipelines or model evaluation infrastructure.
• Experience designing metrics, experiments and quality processes, and turning findings into production systems.
• Strong written communication, attention to detail, and experience working in an early-stage startup.

How to apply

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