Technical Staff Member for Frontier AI Systems

Join a pioneering team dedicated to enhancing AI capabilities through innovative data solutions. As a Member of Technical Staff in Frontier AI, you will play a crucial role in bridging the gap between research, data, and practical AI applications. This hands-on position focuses on improving model and system performance by conducting rigorous evaluations and iterative development.

• Own research and evaluation initiatives from start to finish, including problem framing, data design, quality calibration, and signal validation.
• Design machine learning-oriented data systems, encompassing task definitions, annotation schemas, rubrics, incentives, and pipelines optimized for model performance.
• Analyze model and system failures to identify root causes, edge cases, and opportunities for enhancement.
• Translate ambiguous, real-world behaviors into structured evaluation frameworks and new data categories.
• Collaborate closely with researchers and domain experts to ensure quality calibration and elevate the signal bar continuously.
• Iterate rapidly on evaluations, datasets, and feedback loops to enhance system performance.
• Act as a quality gate by blocking claims, pausing work, or enforcing scope changes when signal strength or data integrity is inadequate.
• Partner with cross-functional and client-facing teams to translate research progress into clear, credible narratives grounded in evidence.
• Identify gaps in data or evaluation coverage and recommend areas for investment, iteration, or cessation based on insights and impact.

• 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 system behaviors into structured research and evaluation opportunities.
• Comfortable operating in ambiguous situations, with a proactive approach to ownership and decision-making.
• Excellent written and verbal communication skills, particularly in articulating trade-offs, limitations, and signal strength to both technical and non-technical stakeholders.
• Proven ability to engage directly with experts during project initiation, calibration, and iteration.
• A systems-level mindset, focused on enhancing overall model or agent performance rather than isolated components.

Full-time position, remote work environment.

Annual salary ranges from $600, 000 to $2, 000, 000.

Open to candidates with relevant experience and skills in AI and machine learning.