Applied Research Intern, Proactive Intelligence & Customer World Models (PhD / Graduate Co-op)

About the role

This is not a traditional internship. You'll own a research problem end-to-end: framing the question, developing methods, running experiments, publishing findings, and, when successful, shipping your work into production systems used by millions of customers and sellers.

Responsibilities

• Work at the intersection of representation learning, foundation models, reinforcement learning, causal reasoning, agentic systems, and product intelligence.
• Focusing on one or more of the following areas:
• Customer World Models
• Proactive Intelligence
• Agentic Decision Systems
• Learning from Feedback Loops
• Evaluation and Measurement

Requirements

• Currently enrolled in an MS or PhD program in Computer Science, Machine Learning, Statistics, Mathematics, Operations Research, or a related field, and returning to that program after the co-op.
• Strong foundations in modern machine learning, including deep learning, optimization, representation learning, and foundation models.
• Experience conducting independent research and translating ideas into working systems.
• Fluency in Python and experience with PyTorch, JAX, or similar frameworks.
• Evidence of research excellence through publications, open-source contributions, technical leadership, or equivalent work.

Nice to have

• Experience with large language models and agentic systems.
• Experience with reinforcement learning, reward modeling, or sequential decision-making.
• Experience with representation learning for structured, temporal, or graph data.
• Familiarity with large-scale training and production ML systems.
• Interest in building AI systems that directly affect customer outcomes.

Benefits

We're looking for researchers interested in building systems that understand people, learn from experience, and improve over time.

Pay

Commensurate with experience.

Schedule

Flexible start September 2026, 8 months duration.