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Quadrillion Labs is hiring a Research Intern to tackle the challenge of training models for research tasks. This position requires owning a research question with minimal guidance and can involve turning research papers into practical applications.
The ideal candidate is enrolled in a PhD program in Computer Science, Statistics, or Linguistics, with proven research experience in machine learning. This role offers competitive compensation and generous benefits, making it a great opportunity for aspiring researchers in an innovative environment.
We're hiring a Research Intern to help us answer a question no one has answered yet: how do you train a model that is genuinely good at research?
This is hard, and largely uncharted. Very few groups have managed to teach LLMs to perform the open-ended, long-horizon reasoning that real research demands: forming a hypothesis, designing an experiment, reading the result, and deciding what to try next. We're doing it with a small team and a strong prior that research data can be used in a highly efficient and ingenious way.
As a Research Intern, you'll own a real research question rather than a ticket. Depending on your interests, that might mean turning a corpus of arXiv papers into reinforcement learning environments, designing reward signals for ambiguous, long-horizon research tasks, building tight RL loops between user data and model training, or constructing research-focused benchmarks.
We work in‑person 5 days a week out of our office in Midtown Manhattan. We cover generous benefits for employees, including medical, dental, and vision insurance, lunch and dinner covered, and other varied stipends.
Quadrillion Labs is an equal opportunity employer. We make hiring and employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, veteran status, or any other characteristic protected by federal, state, or local law. We are committed to building a team where talented people can do their best work.
Compensation Range: $300K - $500K