обновлено 6 дней назад
Staff Research Scientist, AI Agents & LLMs (AI Engineering)
200 000 - 287 500$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
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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