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Member of Technical Staff, Frontier AI

micro1· Core team
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Remote$240k - $350kFull-timePosted 1mo ago

About the role

Technical owner at the intersection of research, data, and real-world AI systems focusing on evaluating and improving model and system performance through rigorous evaluation, failure analysis, and iterative development.

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.
  • Work closely with researchers and domain experts to calibrate quality early and continuously raise the signal bar.
  • Iterate rapidly on evaluations, datasets, and feedback loops to improve system performance.
  • Act as a quality gate: block claims, pause work, or force 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.

Qualifications

  • Strong judgment around research signal quality and when work is (or is not) ready to be externalized.
  • 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, especially when explaining tradeoffs, limitations, and signal strength to technical and non-technical stakeholders.
  • Proven ability to work directly with experts during project kickoff, calibration, and iteration.
  • A systems-level mindset, with interest in improving end-to-end model or agent performance rather than isolated components.

Skills

Required:Research signal quality judgmentDesign ML-oriented datasets and evaluation frameworksTranslate real-world system behavior into evaluation opportunities
Nice to have:RL environments / simulators (preferred)Agentic AI systems experience (preferred)

Benefits

  • Up to 100% reimbursement for health-insurance premiums
  • Paid time off
  • 401(K) plan with company match
  • Additional benefits designed to support a high-performing, remote-first workforce
Last updated Oct 25, 2026. Interested? Apply on the company site.

About micro1

Data lab to train frontier models & evaluate agents

We’re building the infrastructure for advancing intelligence through expert human data, real-world training environments, and contextual evaluations.

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