Member of Technical Staff, Frontier AI
Listing checked September 4, 2026 · pay as published by Micro1
Overview
A full-time remote role at micro1 for a Member of Technical Staff focused on Frontier AI. You’ll bridge research, data design, and live AI systems, driving improvements through careful evaluation and iterative development. You’ll collaborate with researchers, domain experts, and operators to ensure experimental work yields defensible signals that translate into deployed performance gains. Key tasks involve end-to-end research ownership and shaping ML-oriented data pipelines around model impact. Research signal quality, ML data design, and end-to-end evaluation are central to success in this role.
What You'll Do9
- 1Own research and evaluation initiatives from framing through validation, including data design and calibration.
- 2Create ML-oriented data systems with task definitions, annotation schemes, rubrics, incentives, and end-to-end pipelines aimed at boosting model performance.
- 3Analyze model and system failures to uncover root causes, edge cases, and improvement opportunities.
- 4Translate messy real-world behavior into structured evaluation frameworks and new data categories.
- 5Collaborate with researchers and domain experts to maintain early quality gates and continually raise the signal bar.
- 6Iterate quickly on evaluations, datasets, and feedback loops to push system performance forward.
- 7Serve as a quality gate by pausing work or adjusting scope when data or signal strength falls short.
- 8Partner with cross-functional and client-facing teams to present progress with evidence-backed narratives.
- 9Identify data or evaluation gaps and recommend where to invest, iterate, or stop based on impact.
Requirements7
- 1Strong judgment about research signal quality and readiness for external sharing.
- 2Experience designing ML-oriented datasets, evaluation frameworks, and QA processes.
- 3Ability to convert messy real-world behavior into structured research opportunities.
- 4Comfort with ambiguity and a bias toward ownership and decisive action.
- 5Clear written and verbal communication, especially around tradeoffs, limitations, and signal strength to both technical and non-technical audiences.
- 6Proven track record of working with experts during kickoff, calibration, and iteration.
- 7Systems-thinking approach focused on end-to-end model or agent performance rather than isolated components.
Who Should Apply
The ideal candidate brings hands-on experience in evaluating AI systems, building data pipelines for ML tasks, and translating real-world behavior into formal research signals. This role suits someone who thrives in ambiguity, takes ownership, and communicates tradeoffs clearly to varied stakeholders. It may be less suitable for those without a background in reinforcement learning environments, real-world deployments, or evaluating complex, real-time tasks. Common fit checks include the ability to design evaluation frameworks and to demonstrate impact from data design to model performance; candidates lacking these will likely score lower.
Salary Insight
Pay range is $100 - $130 per hour. Pay details are discussed later in the process.
Pay and demand for Machine Learning & AI roles
AggregatedTypical pay
$75/hour
This role
$100–$130/hr
Most Machine Learning & AI roles pay $55–$105 per hour. This role's pay sits above that range.
Based on 442 similar roles that publish pay · 91 publish only a top rate; those count at the rate they gave
Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.
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Most requested skills · share of roles
- python20%
- technical writing10%
- ai evaluation8%
- ai training8%
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Compensation
$100–130/hr
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