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4 дня назад

Senior Regional Player-Coach (AI)

150 000 - 300 000$
Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Релокация
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Senior Regional Player-Coach (AI): Building and leading applied research programs for frontier AI post-training, agents, evaluations, and deployed systems with an accent on external partner programs, experimental rigor, and recruiting a New York research group. Focus on designing environments and reward signals, debugging training and evaluation loops, attributing failures, and turning validated results into shared research or product capabilities.

Location: Full-time, in-person work from the New York City office; relocation support and visa sponsorship are available.

Salary: $150,000–$300,000 cash compensation plus equity incentives.

Company

hirify.global is building an open superintelligence stack combining compute, environments, evaluations, secure sandboxes, high-performance training, and deployment for frontier AI post-training.

What you will do

  • Establish the New York Applied Research group through personally led research and external field programs.
  • Shape customer and partner problems into research programs with clear owners, comparable evidence, and paths to shared capabilities.
  • Lead high-stakes programs through environment design, baselines, post-training, evaluation, failure analysis, and deployment.
  • Recruit and develop the founding New York researchers while setting technical and experimental standards.
  • Provide cross-program technical direction and decide which results become shared research, open-source systems, or product capabilities.

Requirements

  • Track record leading high-performing applied-research or research-engineering teams.
  • Deep credibility in reinforcement learning, post-training, agents, evaluation, or machine learning systems.
  • Exceptional recruiting judgment and experience with demanding external technical stakeholders.
  • Hands-on experience building and debugging model-training, post-training, agent, evaluation, or closely adjacent experimental loops.
  • Strong experimental judgment, including meaningful baselines, careful trace inspection, clear failure attribution, and willingness to change direction when evidence changes.
  • Strong Python skills and the ability to build artifacts that other researchers and engineers can run, inspect, and extend.
  • Ability to own ambiguous problems and keep partners and teammates current while resolving them.
  • Willingness to remain directly involved in research, external programs, recruiting, and group development.

Nice to have

  • Publications, open-source systems, benchmarks, or shipped products demonstrating exceptional work.

Culture & Benefits

  • In-person work from the New York City office.
  • Professional development budget.
  • Team off-sites and conference attendance.
  • Equity incentives.
  • Visa sponsorship and relocation support.

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