Remote | Research Experts for Frontier AI/ML Open Questions — Up to $90/hr

We are sharing a specialised part-time consulting opportunity for exceptional PhD students and postdoctoral researchers with deep expertise in AI, machine learning, and adjacent engineering fields.

This role supports a leading intelligence AI laboratory working to identify the most important open questions in core AI and machine learning fields and to build structured knowledge bases that could meaningfully accelerate progress over the next decade.

Selected professionals will help identify transformative research questions, evaluate their tractability and significance, and build structured expert knowledge bases containing seminal papers, datasets, methods, recent advances, and expert commentary relevant to those questions.

Key Responsibilities

Professionals in this role may contribute to:

Open Question Identification
Propose major open research questions in AI, machine learning, or adjacent engineering fields where a breakthrough would be highly transformative
Focus on problems that are concrete, tractable, and closely aligned with personal domain expertise
Apply strong judgment to distinguish questions with real breakthrough potential from overly broad or purely speculative topics

Knowledge Base Development
Build structured knowledge bases for selected open questions
Curate seminal papers, key datasets, methods, recent advances, and less widely recognised but valuable sources
Organise literature into clear expert learning paths relevant to major research questions

Expert Synthesis & Commentary
Provide brief expert commentary explaining why each source, approach, or method matters
Help define how meaningful progress on a selected question could be evaluated
Contribute structured reasoning about significance, tractability, and research quality across complex technical areas

Ideal Profile

Strong candidates may have:
Current status as a PhD candidate or postdoctoral researcher
Affiliation with a top-tier institution
Deep expertise in AI, machine learning, engineering, or a closely related technical field
Strong judgment about research significance, tractability, and quality
Ability to synthesise large bodies of literature into clear, structured learning paths
Clear point of view on which open questions truly matter in their field

Preferred qualifications

Experience conducting high-level literature reviews or knowledge synthesis in frontier AI or ML domains
Ability to mentor or guide other experts toward meaningful progress on adjacent questions
Strong familiarity with seminal and recent literature in a specialised research area
Ability to identify research questions where progress is both measurable and plausible within the next decade
Comfort preparing structured reading lists with expert-level commentary

Why This Opportunity

Contribute directly to identifying the open questions that could shape the future of AI and machine learning
Help build structured expert knowledge bases designed to accelerate progress over the next decade
Apply deep research expertise in a highly selective and intellectually rigorous environment
Flexible remote work with competitive compensation

Contract Details

Independent contractor role
Fully remote with flexible scheduling
Compensation range of $80–$90 per hour
Time commitment of approximately 8–16 hours per selected question
Weekly payments via Stripe or Wise
Projects may be extended, shortened, or concluded early depending on project needs and performance
Work will not involve access to confidential or proprietary information from any employer, client, or institution
Please note: We are unable to support H1-B or STEM OPT candidates at this time
A short eligibility form is required in addition to the AI interview during the application process

About the Platform

This opportunity is available through a leading AI-driven work platform that connects domain experts with frontier AI research projects.

Experts contribute to improving advanced AI systems by providing specialised expertise across research synthesis, technical reasoning, structured evaluation, and domain-specific knowledge development.

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