Назад
9 дней назад

Member of Technical Staff in Post-Training (LLM/RL)

295 000 - 535 000CAD
Формат работы
remote (Global)
Тип работы
fulltime
Английский
b2
Страна
US/Europe/Canada
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
Member of Technical Staff in Post-Training (LLM/RL): Training large language models with reinforcement learning and developing methods for out-of-distribution generalization with an accent on reward design, diverse environments, and rigorous evaluation. Focus on building held-out evaluations, diagnosing reward hacking and training instability, and turning successful research into reproducible production training recipes.

Location: Remote or from offices in Europe, New York, or Toronto; no minimum in-office requirement, with core time zone and working-hours alignment expected based on the listed location.

Salary: Canada — Toronto and Montreal: CA$295K–CA$535K base salary; USA — New York, California, and Washington: $205K–$380K base salary; other US states: $175K–$325K base salary. Equity is offered.

Company

Cohere builds security-first enterprise AI models and end-to-end products for real-world business applications.

What you will do

  • Design, run, and analyze large-scale reinforcement learning post-training experiments, including RLHF and reinforcement learning from verifiable rewards.
  • Research methods for improving out-of-distribution generalization through reward design, diverse environments and tasks, curricula, and regularization.
  • Build held-out evaluations for unseen tasks, domains, and formats while detecting reward hacking and benchmark overfitting.
  • Diagnose training dynamics and failure modes such as instability, reward over-optimization, and capability regressions.
  • Convert successful research into robust, reproducible training recipes for production models.
  • Collaborate with post-training data infrastructure, evaluation, and pre-training teams.

Requirements

  • Strong research and software engineering skills with hands-on experience training large language models.
  • Experience applying reinforcement learning to LLMs, such as PPO, GRPO, RLHF, or RLVR, ideally at scale.
  • Research or shipped-model experience in generalization, robustness, or distribution shift.
  • Rigorous experimental practice, including clean ablations, careful controls, and sound conclusions from noisy results.
  • Excellent communication skills and a deep understanding of data quality and dataset impact on model training.

Nice to have

  • Experience with distributed training technologies such as JAX, PyTorch, FSDP, or Megatron.

Culture & Benefits

  • Remote-friendly work with offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin, and Seoul.
  • Weekly lunch stipend of $75, £75, or equivalent in local currency.
  • Health and dental benefits, mental health budget, RRSP matching, 401K, and pension scheme.
  • Six weeks of paid vacation, parental leave top-up for up to six months, and annual enrichment benefits.
  • Education and learning stipend, coworking benefit, home office stipend, and travel budget for remote employees.
  • Annual company offsite and office-based lunch, social, and community programs.

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