Applied Research Intern, Proactive Intelligence & Customer World Models

This is a fully remote position, open to applicants in Canada, +1 more country.

📋 Description

• Take ownership of a research problem from start to finish: define the question, devise methodologies, conduct experiments, publish results, and potentially integrate work into production systems.

• Create comprehensive customer profiles utilizing event streams, financial transactions, operational signals, and behavioral data.

• Design proactive intelligence systems that foresee customer needs and trigger beneficial actions.

• Develop agents that analyze customer world models and perform actions in real-world environments.

• Create techniques for reinforcement learning based on customer and product feedback, reward modeling, preference learning, counterfactual evaluation, and long-term credit assignment.

• Establish evaluation frameworks to assess real-world performance, trustworthiness, and customer value.

• Collaborate across various domains including representation learning, foundational models, reinforcement learning, causal reasoning, agent systems, and product intelligence.

⛳️ Requirements

• Currently pursuing an MS or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Operations Research, or a related discipline, and planning to return to that program after the co-op.

• Strong grounding in contemporary machine learning, covering deep learning, optimization, representation learning, and foundational models.

• Proven experience in conducting independent research and translating concepts into functional systems.

• Proficiency in Python and familiarity with frameworks like PyTorch, JAX, or similar.

• Demonstrated research excellence through publications, open-source contributions, technical leadership, or comparable work.

• Experience with large language models and agent systems.

• Familiarity with reinforcement learning, reward modeling, or sequential decision-making processes.

• Knowledge of representation learning for structured, temporal, or graph-based data.

• Understanding of large-scale training and production machine learning systems.

• Passion for developing AI systems that directly influence customer outcomes.

🏝️ Benefits

• Direct mentorship from researchers focused on the future of proactive intelligence at Block.

• Access to extensive datasets, modern infrastructure, cutting-edge models, and significant computational resources.

• Opportunities to publish research and contribute to open-source initiatives.

• A chance to influence foundational technology that may drive the next generation of Block products.

• Exposure to both scientific research and product implementation, with a clear pathway from concept to impact.

• Remote work options available.

• Medical insurance coverage.

• Flexible vacation policies.

• Retirement savings plans.

• Modern family planning benefits.