Technical Staff Member for Frontier AI Systems [Remote]

This role focuses on enhancing model and system performance through rigorous evaluation and iterative development. As a Member of Technical Staff, you will operate at the intersection of research, data, and real-world AI systems, ensuring that experimental work yields clean, defensible research signals that lead to meaningful improvements in deployed systems. Key Responsibilities

• Own research and evaluation initiatives end-to-end: problem framing, data design, quality calibration, and signal validation.
• Design ML-oriented data systems, including task definitions, annotation schemas, rubrics, incentives, and pipelines optimized for downstream model performance.
• Analyze model and system failures to identify root causes, edge cases, and opportunities for improvement.
• Translate ambiguous, real-world behavior into structured evaluation frameworks and new data categories.
• Collaborate closely with researchers and domain experts to calibrate quality and continuously raise the signal bar.
• Iterate rapidly on evaluations, datasets, and feedback loops to enhance system performance.
• Act as a quality gate: block claims, pause work, or enforce scope changes when signal strength or data integrity is insufficient.
• 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 where to invest, iterate, or stop based on learnings and impact.

• Strong judgment regarding research signal quality and readiness for externalization.
• Experience designing ML-oriented datasets, evaluation frameworks, and QA processes.
• Ability to translate messy, real-world system behavior into structured research and evaluation opportunities.
• Comfort operating in ambiguity, with a bias toward ownership and decisive action.
• Clear written and verbal communication skills, especially in explaining tradeoffs, limitations, and signal strength to both technical and non-technical stakeholders.
• Proven ability to work directly with experts during project kickoff, calibration, and iteration.

Full-time position, remote work environment.

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

Open to candidates with relevant experience and skills in the field.