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обновлено 6 дней назад

Staff Research Scientist, AI Agents & LLMs (AI Engineering)

200 000 - 287 500$
Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Staff Research Scientist, AI Agents & LLMs (AI Engineering): Building models and systems that turn enterprise data into self-directed, decision-making agents with an accent on autonomous agents and large language models (LLMs). Focus on reliable reasoning, long-horizon planning, grounded generation, and scalable model and agent development.

Location: Hybrid in Bellevue, Washington or Menlo Park, California, United States

Salary: $200,000–$287,500 per year

Company

Snowflake provides an enterprise Data Cloud platform and develops AI, data, and machine learning products.

What you will do

  • Define research direction in agentic AI and large language models.
  • Train, fine-tune, align, and develop models for enterprise reasoning and tool use.
  • Advance autonomous agents, multi-step reasoning, tool use, retrieval, grounding, memory, and multi-agent coordination.
  • Establish evaluation standards for reliability, safety, and efficiency.
  • Drive research breakthroughs into production within Snowflake’s platform.
  • Mentor researchers, provide technical leadership, and contribute through publications and open source.

Requirements

  • Ph.D. in Computer Science or a related field with a strong publication record.
  • Expertise in large language model development, including training, fine-tuning, alignment, or post-training.
  • Experience with agentic systems, including multi-agent systems, tool use, or agent optimization.
  • Strong systems thinking under real-world latency, cost, and reliability constraints.
  • Proven technical leadership and end-to-end ownership.
  • Ability to translate research into impactful production systems.

Culture & Benefits

  • Work across the full AI stack, from foundation models to production systems.
  • Conduct frontier research using enterprise data and production workloads.
  • Build autonomous systems for reliable reasoning over enterprise data.
  • Publish research and contribute to open-source projects.
  • Follow strict confidentiality and data security standards when handling sensitive customer information.

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