Research Scientist

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OpenRouter

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2023

🤖 Artificial Intelligence

☁️ SaaS

📚 Education

Artificial Intelligence • SaaS • Education

OpenRouter is a platform providing a unified interface for interacting with various large language models (LLMs). It focuses on delivering better prices and uptime without the need for subscriptions. The platform supports multiple AI tasks and showcases models like Mistral Small 3 and DeepSeek R1 Distill Qwen 32B, which are designed for fast performance and high accuracy. OpenRouter also features gaming and coding tools that enhance usability across different sectors such as marketing, finance, and education.

📋 Description

• Own and pursue a research agenda focused on LLM evaluation, model quality, routing optimization, and AI usage patterns, contributing original insights that advance the field. • Design novel evaluation frameworks and benchmarks that go beyond standard leaderboards, using real-world generation data to capture how models actually perform across tasks and contexts. • Conduct large-scale empirical studies on LLM behavior: how models compare across providers, how performance changes over time, and how usage patterns reveal strengths and weaknesses. • Develop the statistical and mathematical foundations behind our routing systems, building the models and heuristics that power intelligent provider and model selection. • Identify opportunities to apply research findings to feed back into OpenRouter's product and platform. • Collaborate with external researchers, model providers, and the open-source community to advance shared understanding of LLM capabilities and limitations. • Work with product and engineering teams to translate research findings into improvements to OpenRouter's platform, without being constrained to a shipping cadence.

🎯 Requirements

• MS or PhD in a quantitative field (machine learning, statistics, computer science, mathematics, computational linguistics, or similar). • Track record of original research, demonstrated by first-author publications, significant open-source contributions, or equivalent impact in industry research. • Deep expertise in statistics, experimental design, and causal inference. You can design rigorous studies and reason carefully about validity, bias, and generalizability. • Strong programming skills in Python. You can build data pipelines, run large-scale experiments, and prototype models efficiently. • Proficiency in SQL for working with large-scale analytical databases (ClickHouse, BigQuery, or similar). • Hands-on experience with modern ML/NLP techniques such as LLM evaluation, fine-tuning, embeddings, classification, or reinforcement learning from human feedback. • Familiarity with the current LLM landscape: model architectures, provider ecosystems, benchmark suites, and the strengths and limitations of leading models.

🏖️ Benefits

• Health insurance • Flexible working arrangements • Professional development opportunities