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

What you'll do

• Frame research problems, develop methods, run experiments, and publish findings.
• Build customer representations, proactive decision systems, agents, or learning and evaluation methods.
• Translate successful research into production systems.

What they ask for

• Currently enrolled in an MS or PhD program in Computer Science, Machine Learning, Statistics, Mathematics, Operations Research, or a related field, and returning to the 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; 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.

Tools

Python, PyTorch, JAX

AI focus

Research and develop customer world models, proactive intelligence, agentic decision systems, learning from feedback, and evaluation methods for AI systems that anticipate customer needs and improve over time.