Description
At Scale, our mission is to develop reliable AI systems for the world's most important decisions.
As an intern on the Machine Learning Research team, you'll work on a combination of deeply technical ML applications in production and cutting-edge research problems, with mentorship from world-class researchers and the opportunity to collaborate with leading teams across industry and academia.
Example Projects
- Measure the dangerous capabilities of frontier models and conduct preparedness research
- Research the science and creation of new benchmarks for frontier models
- Develop new methods for training models to excel on extremely difficult reasoning problems that require long chains of thought
- Research reinforcement learning and post-training methods that improve model reliability on high-stakes tasks
- Research scalable oversight protocols that enable humans to produce and quality control reasoning chains beyond their native capabilities
- Study the boundaries of model generalization and capabilities to inform data-driven advancements
- Research synthetic and hybrid data with humans in the loop to scale up high-quality data generation
- Take models currently in production, identify areas for improvement, improve them using retraining and hyperparameter searches, then deploy without regressing on core model characteristics
- Create post-training or agentic solutions that integrate into our ability to deliver applications for enterprise and public sector clients
Required to Have
- Currently enrolled in a BS, MS or PhD program with a focus on Machine Learning, Deep Learning, or Natural Language Processing, with a graduation date in Fall 2027 or Spring 2028
- Available for a Summer 2027 internship (May/June start dates) in San Francisco Or New York
- Prior research experience or a track record of publications on LLMs, NLP, multimodal models, agents, safety, evaluation, alignment, or a related field
- Experience with one or more general purpose programming languages, including Python, Javascript, or similar
Ideally You'd Have
- A previous internship in Machine Learning, Deep Learning, Natural Language Processing, Adversarial Robustness, Alignment, Evaluation, or Agents
- Experience as a researcher , through internships, full-time roles, or at a lab
- Publications at top-tier venues such as NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP or AAAI, or contributions to open source projects
- Hands-on experience with reinforcement learning, agentic systems, or evaluation infrastructure
How We Work
Our credos shape how we make decisions and work as a team:
- Earn Customer Love , trust is earned with every interaction, every delivery, and every problem we solve
- Team Flow , ideas, energy, and support move freely across teams; optimize for the whole
- Quality is Our Cheat Code , the systems that deliver quality consistently are a structural advantage
- Find the 20% , find the inputs that drive the outcomes and execute them completely
- Write the Market , our research puts us at the frontier, and we bring our partners there first
- Three Moves Ahead , consider the consequences of consequences, and plan accordingly
Compensation
The base salary range for this full-time position in the locations of San Francisco and New York is: $120,000-$150,000 USD. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO.