2 дня назад
Research Scientist (LLM)
250 000 - 285 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Research Scientist (LLM) (AI/ML): Conducting original research on LLM evaluation, model quality, routing optimization, and AI usage patterns using large-scale generation data, with an accent on experimental design, statistical modeling, and causal inference. Focus on designing benchmarks, studying model behavior across providers and contexts, and developing the mathematical foundations for intelligent model and provider selection.
Location: Remote (US)
Salary: $250,000–$285,000 per year, plus equity
Company
provides an AI routing and infrastructure layer for accessing, managing, and optimizing large language models across providers.
What you will do
- Own a research agenda focused on LLM evaluation, model quality, routing optimization, and AI usage patterns.
- Design evaluation frameworks and benchmarks using real-world LLM generation data.
- Conduct large-scale empirical studies of model behavior, provider differences, performance changes, and usage patterns.
- Develop statistical and mathematical models, heuristics, and foundations for intelligent model and provider selection.
- Apply research findings to improve ’s product and platform.
- Collaborate with external researchers, model providers, open-source communities, and internal product and engineering teams.
Requirements
- MS or PhD in machine learning, statistics, computer science, mathematics, computational linguistics, or a similar quantitative field.
- Track record of original research through first-author publications, significant open-source contributions, or equivalent industry research impact.
- Expertise in statistics, experimental design, and causal inference.
- Strong programming skills in Python and proficiency in SQL for large-scale analytical databases such as ClickHouse or BigQuery.
- Hands-on experience with LLM evaluation, fine-tuning, embeddings, classification, or reinforcement learning from human feedback.
- Familiarity with LLM architectures, provider ecosystems, benchmark suites, and the strengths and limitations of leading models.
Culture & Benefits
- Research quality and impact are prioritized over production code delivery or dashboard development.
- Self-directed work with high scientific standards and startup-speed execution.
- Frequent use of LLMs, coding agents, and modern AI tools in research workflows.
- Collaboration with product and engineering teams to turn research findings into actionable recommendations.
- Equity is offered in addition to the stated compensation.
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