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.
What you'll do
- Post-train models for scientific and computational research tasks
- Build evaluations and benchmarks for such tasks, and use them to measure frontier models and our own
Required qualifications
- Currently enrolled in a PhD program in Computer Science, Statistics, or Linguistics
- Research experience in at least one area of machine learning or its neighbors (natural language processing, deep learning, reinforcement learning, optimization, statistics, etc.)
- Ability to move quickly in a zero-to-one environment
Preferred qualifications
- A track record of research contributions, such as first-author publications at major ML conferences (NeurIPS, ICML, ICLR) or strong journals.
- Hands-on experience training, fine-tuning, or benchmarking large modern models.
- Enrolled at a degree program in the US or Canada, returning to the program after the internship.
About this role
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. We pride ourselves on a company culture that values a diversity of thoughts and opinions.
About Quadrillion
Quadrillion Labs builds Qualia, an agentic research intelligence platform that does real computational research — running experiments, analyzing data, and surfacing insight for the people who do this work at the highest level. We're a team out of Stanford NLP, HRT, Citadel, Jane Street, Google Research, and Harvard Med, building for an audience that looks a lot like us. We've raised ~$18M from Conviction, Audacious, Bloomberg Beta, ex/ante, and angels including Wes McKinney, the creator of pandas. We're ~10 people in NYC, scaling to ~15 in the coming months. We think this is the Industrial Revolution moment for research, and we're building the team to define what comes next.
Equal Employment Opportunity 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. If you need a reasonable accommodation during the application or interview process, let us know at careers@quadrillion.io.
