Research Scientist

Required

• 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.
• Mindset & Approach
• Deeply curious and self-directed. You identify the most important open questions and pursue them without waiting for direction.
• Rigorous but pragmatic. You hold yourself to high scientific standards while operating at startup speed.
• AI-first in your own workflow. You use LLMs, coding agents, and modern AI tools heavily in your research process and have strong opinions about what works.
• Strong communicator. You can explain complex findings clearly in papers, blog posts, internal memos, and conversations with non-technical stakeholders.