AI & Emerging technologies

ML Engineer

Great Value Hiring

Remote · Nationwide · Canada

Research Experts for Frontier AI/ML Open Questions ($80-$90/hr)

Exceptional PhD students and PostDocs with a clear point of view on what problems truly matter in their field and the depth to define how those problems could be tackled.

Role Responsibilities

  • Identify high-impact open questions
  • Propose major open questions where a breakthrough would be transformative
  • Focus on problems that are concrete, tractable, and close to your expertise
  • Build a knowledge base for selected questions
  • Seminal papers, key datasets, methods, recent advances, and “hidden gems”
  • Assume an extremely strong expert all knowledge up until 6 months ago (1st October, 2025)

Time commitment

~8–16 hours per selected question

Good Candidature

  • PhD candidates or PostDocs from top-tier institutions
  • Deep expertise in AI/ML/Engineering
  • Strong judgment about significance, tractability, and research quality
  • Ability to synthesize large bodies of literature into clear learning paths

Expected Outputs

  • Clearly articulated, high-impact open research questions
  • Structured reading lists (~30–100 sources per question)
  • Brief expert commentary on why each source and approach matters

Eligibility Requirement

You will need to fill a short form in order to be eligible for this role:

Consider the biggest open questions in your field, for example, the 10–15 questions where a breakthrough would make headline news. From this set, select those closest to your area of expertise: questions within or adjacent to your specialty or those where you could mentor an expert toward meaningful progress.

Specifically, We Are Looking For Questions Where

  • A major breakthrough would be widely recognized as transformative (e.g., headline news in Nature, Science, or top field-specific venues)
  • Meaningful progress is plausible within the next decade (not purely speculative or dependent on unknown technology)
  • The question is concrete enough that progress can be evaluated (avoid umbrella questions like “How does the ML work?”)
  • You have the relevant expertise to assemble a comprehensive knowledge base directly relevant to the question

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Reference: WJ-4483_1399589

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