Member of Technical Staff, Frontier AI

Role Responsibilities

• Own research and evaluation initiatives end-to-end, including problem framing and signal validation.
• Design ML-oriented data systems with optimized task definitions and annotation schemas.
• Analyze model and system failures to identify root causes and opportunities for improvement.
• Translate real-world behavior into structured evaluation frameworks and new data categories.
• Collaborate with researchers and domain experts to continuously raise the signal bar.
• Iterate on evaluations and feedback loops to enhance system performance.
• Act as a quality gate to ensure data integrity and signal strength.
• Persuade cross-functional teams to translate research progress into credible narratives.

Requirements

• Strong judgment around research signal quality and readiness for externalization.
• Experience designing ML-oriented datasets and evaluation frameworks.
• Ability to translate real-world system behavior into structured research opportunities.
• Comfort operating in ambiguity with a bias toward ownership and decisive action.
• Clear communication skills for explaining tradeoffs and signal strength.
• Proven ability to work with experts during project kickoff and iteration.
• A systems-level mindset focused on improving end-to-end model performance.