Compensation: $600,000–$2,000,000/yr
Location: Remote
Employment Type: Full-time
Updated: Jun 20, 2026
Join a dynamic team as a Member of Technical Staff focused on enhancing AI capabilities through rigorous evaluation and innovative data design. This role is pivotal in bridging the gap between research and real-world AI applications, ensuring that foundational models and AI agents are trained effectively using high-quality data and evaluations.
Own research and evaluation initiatives from problem framing to signal validation.
Design ML-oriented data systems, including task definitions, annotation schemas, and pipelines optimized for model performance.
Analyze model and system failures to identify root causes and opportunities for improvement.
Translate ambiguous real-world behavior into structured evaluation frameworks and new data categories.
Collaborate with researchers and domain experts to continuously enhance quality and signal strength.
Rapidly iterate on evaluations, datasets, and feedback loops to boost system performance.
Act as a quality gate, managing claims and ensuring data integrity.
Work with cross-functional teams to communicate research progress effectively.
Identify gaps in data or evaluation coverage and recommend strategic actions based on insights.
Strong judgment regarding research signal quality and readiness for externalization.
Experience in designing ML-oriented datasets, evaluation frameworks, and quality assurance processes.
Ability to convert complex real-world behaviors into structured research opportunities.
Comfort in ambiguous situations with a proactive approach to ownership and decision-making.
Excellent written and verbal communication skills, particularly in explaining technical concepts to diverse stakeholders.
Proven experience collaborating with experts during project initiation and iteration.
A systems-level mindset focused on enhancing overall model or agent performance.
Full-time position with remote work flexibility.
Open to qualified candidates without specific visa restrictions.
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