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4 часа назад

AI Researcher (LLMs)

200 000 - 300 000$
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
UK/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
AI Researcher (LLMs) (LLM research): Building large language models from scratch for research, engineering, and trading workflows with an accent on pretraining, post-training, evaluation, and inference. Focus on designing impactful ablations, driving frontier capability gains, and deploying models into live trading.

Location: London, United Kingdom, or New York, NY, United States

Base salary: USD 200,000–300,000 per year, plus discretionary performance-based bonuses and a competitive benefits package.

Company

hirify.global applies scientific methods and sophisticated computing infrastructure to algorithmic trading.

What you will do

  • Develop large language models from scratch for research, engineering, and trading workflows.
  • Work across tokenizer training, dataset curation and mixing, pretraining, post-training, evaluation, inference, and live trading.
  • Design experiments and ablations that guide research decisions and produce frontier capability gains.
  • Deploy research code and models across the firm in collaboration with engineering, hardware, and systems teams.
  • Operate independently within a small, focused AI research team.

Requirements

  • At least two years of hands-on experience training, post-training, or evaluating LLMs at scale.
  • Direct experience with large-scale pretraining, post-training such as SFT or RL, LLM evaluation design and statistical analysis, or distributed training and inference systems.
  • Ability to identify promising research directions, design decision-changing ablations, and update conclusions based on evidence.
  • Strong engineering skills in GPU kernel development, lower-level PyTorch internals, or frontier-style LLM research.

Culture & Benefits

  • Access to advanced research clusters with a high GPU-to-researcher ratio.
  • Support from dedicated engineering, hardware, and systems teams.
  • Open and transparent environment with significant researcher independence and minimal bureaucracy.
  • Collaborative culture that values diverse expertise, new ideas, and togetherness.
  • Competitive benefits package and discretionary performance-based bonuses.

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