Remote Principal Research Scientist - Frontier AI

YO AI Labs

New York (NY)

Remote

USD 120.000 - 190.000

Vollzeit

Vor 2 Tagen
Sei unter den ersten Bewerbenden

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

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Zusammenfassung

YO AI Labs in the United States invites experienced Principal Research Scientists in Computer Science or Computational Physics for an AI research project. You will work remotely on frontier models to explore open problems, validate results, and advance theoretical and computational research.

No prior AI experience is required. You will identify foundational problems, guide models through proofs, numerical experiments, and HPC simulations, and document findings with memos.

Qualifikationen

  • 7-10+ years of active research in CS, mathematical physics, or computational physics.
  • Strong record of scholarly publications in leading venues within the last year.
  • Expertise in computational methods: simulation, numerical analysis, algorithms, or HPC.

Aufgaben

  • Identify foundational open problems and simulation challenges with verifiable outcomes.
  • Guide AI models through research tasks including proofs, algorithms, and numerical experiments.
  • Validate results via reproduction, formal methods, and rigorous evaluation.
  • Assess novelty, correctness, and significance relative to the literature.
  • Document findings in research memos and highlight AI model limitations.
  • Suggest promising directions and open problems for AI-assisted research.

Kenntnisse

Research experience
Numerical analysis
High-performance computing
Publications in leading venues
Theoretical reasoning

Jobbeschreibung

YO AI Labs in the United States invites experienced Principal Research Scientists in Computer Science or Computational Physics for an AI research project. You will work remotely on frontier models to explore open problems, validate results, and advance theoretical and computational research.

No prior AI experience is required. You will identify foundational problems, guide models through proofs, numerical experiments, and HPC simulations, and document findings with memos.

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