Open-Source AI Research Platform Lead (Remote/Hybrid)

Prime Intellect, Inc.

United States

Remote

USD 150.000 - 300.000

Vollzeit

vor 34 Stunden
Sei unter den ersten Bewerbenden

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

Schaffe es an den ATS-Filtern vorbei

Benefits dieser Stelle

Visa sponsorship
Relocation support
Professional development budget

Zusammenfassung

Prime Intellect, Inc. is seeking a researcher to own the path from emerging research artifact to a robust open-source and product experience.

You will contribute to open-source RL, environment, evaluation, and agent systems, and build researcher-facing features in a training platform with engineering and design support. You will provide APIs, examples, reference implementations, and explanations that expose useful abstractions, enabling researchers and engineers to run and extend work.

Qualifikationen

  • Experience owning open-source ML or developer-tool systems.
  • Hands-on experience building and debugging model-training, post-training, agent, or evaluation loops.
  • Strong Python and the ability to build artifacts that other researchers and engineers can run and extend.

Aufgaben

  • Own open-source RL, environment, evaluation, and agent systems.
  • Researcher-facing features in our training platform, built with engineering and design.
  • APIs, examples, reference implementations, and technical explanations that expose useful abstractions.

Kenntnisse

Python
Open-source ML
Research tooling
Model training loops
Post-training evaluation
Bug debugging

Jobbeschreibung

Prime Intellect, Inc. is seeking a researcher to own the path from emerging research artifact to a robust open-source and product experience.

You will contribute to open-source RL, environment, evaluation, and agent systems, and build researcher-facing features in a training platform with engineering and design support. You will provide APIs, examples, reference implementations, and explanations that expose useful abstractions, enabling researchers and engineers to run and extend work.

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