Year-Round Intern - AI Research & Engineering

20 hours ago

Responsibilities

Build and iterate on AI agent workflows for OCC functional areas.
Integrate agentic AI solutions with internal data sources and APIs using MCP and tool-use patterns.
Design test cases and evaluation frameworks for agent accuracy, reliability, and safety.
Support AI governance and risk-review processes for proposed use cases.
Document agent architectures, prompt designs, and lessons learned.
Collaborate with business stakeholders to gather requirements and validate solutions.

Be an actively enrolled rising senior or second-year graduate student graduating in December 2027 or May/August 2028.
Pursue a relevant major such as computer science, data science, statistics, mathematics, engineering, physics, machine learning, financial engineering, economics, or a related field.
Have solid programming skills in Python and/or SQL, Java, C++, or R.
Have coursework or project experience in machine learning, AI, or data science.
Have exposure to PyTorch, TensorFlow, or Scikit-learn, and interest or experience with generative AI, LLMs, prompt engineering, or agentic systems.
Familiarity with AWS, Azure, GCP, Spark, Databricks, data pipelines, or data engineering tools is desired.
Demonstrate strong analytical, problem-solving, communication, initiative, and self-directed learning skills.
Prior technical or analytical internship/work experience, strong academic performance, and familiarity with collaborative development practices are preferred.

Paid sick leave accrued based on hours worked; interns are not eligible for other benefits or the technology stipend.
Year-round internship runs January 2027 through December 2027, with a maximum of 1,000 hours.
Interns may work up to 20 hours per week during the school year and up to 40 hours per week during the summer; overtime is not permitted.
Hybrid work arrangement based in Chicago, generally requiring at least three office days per week, with Tuesday and Wednesday as anchor days.