Applied Research Intern, Proactive Intelligence & Customer World Models
New
B
BlockAI research
Remote (US / Canada)InternshipEntry
Salary not disclosed
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Job Details
- Required Skills
- PythonMachine LearningPyTorchDeep Learning
Requirements
- Be currently enrolled in an MS or PhD program in Computer Science, Machine Learning, Statistics, Mathematics, Operations Research, or a related field.
- Return to the graduate program after the co-op.
- Have strong foundations in modern machine learning, including deep learning, optimization, representation learning, and foundation models.
- Have experience conducting independent research and translating ideas into working systems.
- Be fluent in Python.
- Have experience with PyTorch, JAX, or similar frameworks.
- Show 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.
- Nice to have: experience with reinforcement learning, reward modeling, or sequential decision-making.
- Nice to have: experience with representation learning for structured, temporal, or graph data.
- Nice to have: familiarity with large-scale training and production ML systems.
Responsibilities
- Build rich customer representations from event streams, financial activity, operational signals, and behavioral data.
- Develop systems that anticipate customer needs and initiate helpful actions.
- Build agents that reason over customer world models and take actions in real environments.
- Develop methods for learning from customer and product outcomes, including reinforcement learning and preference learning.
- Build evaluation frameworks to predict real-world performance, trust, and customer value.
- Frame research questions, develop methods, and run experiments.
- Publish findings and, when successful, ship research into production systems.
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