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CBRE · 4 months ago

Machine Learning Intern, Regulatory

Chicago, IL

Internship

Hybrid

Intern

$22/hr - $42/hr

Cboe Global Markets is a leading provider of market infrastructure and tradable products, seeking a Machine Learning intern to work on prototyping and validating machine learning models for market surveillance. The role involves collaborating with experts, preparing data, and contributing to innovative solutions in a fast-paced financial environment.

CommercialFinancial ServicesProperty DevelopmentReal Estate

No H1B

U.S. Citizen Only

Responsibilities

Train various candidate models to fit a given business problem

Prepare data sets and design data features for ML input in conjunction with financial surveillance experts

Effectively track and evaluate ML model performance during research phase

Contribute creative ideas for problem solving during brainstorming discussions with ML team and users

Receive and implement constructive feedback through rigorous code reviews, QA testing, and model evaluation

Work in both on-premises and cloud environments

Produce clear and thorough documentation for your research and analytical work

Communicate technical information clearly and concisely to an end-user audience

Learn best practices in software engineering and ML research

Qualification

Machine LearningPythonData EngineeringSQLStatistical TechniquesDeep LearningLarge Language ModelsCommunication SkillsCritical ThinkingAttention to Detail

Required

Candidates must be enrolled in a university or college program and should not be scheduled to graduate before December of the internship year

Extreme intellectual curiosity, tolerance for uncertainty, perseverance

Good academic knowledge of machine learning models (classical, deep learning, and LLMs) and statistical techniques

Strong programming and large-scale data engineering skills

Understanding of a wide variety of machine learning algorithms, supervised and unsupervised, classical and deep learning, including modern large language models and their unique infrastructure requirements

Fluency with advanced undergraduate-level mathematics, including statistics, linear algebra, and multivariable calculus

Familiarity with writing code to support the various lifecycle phases of machine learning projects such as training, validation, inference, and production monitoring

Strong Python-based programming and data engineering skills

Strong SQL knowledge (Snowflake experience is a plus)

Experience with common data science and ML libraries, such as numpy, pandas, Spark, scikit-learn, TensorFlow, and PyTorch

Experience configuring and using AI agents to assist with coding and research tasks

Experience developing and deploying AI agents/workflows for knowledge-intensive tasks with stringent correctness requirements

Ability to work both independently and as part of a team

Excellent written and verbal communication skills

Demonstrates critical thinking, attention to detail, and good judgment

Bachelor's or Master's degree in progress in a quantitative field and should not be scheduled to graduate before December of the year in which the internship takes place