Machine Learning Intern, Regulatory

Cboe Global Markets is a leading provider of market infrastructure and tradable products, dedicated to solving complex challenges in the financial sector. The Regulatory Machine Learning intern will work on prototyping, training, testing, and validating machine learning models to enhance the surveillance of financial markets, while gaining valuable experience in a fast-paced environment.

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

Skills

• 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
• Strong ability to translate and see long-range connections between trade-offs in ML algorithm design and trade-offs in end-user product features
• Knowledge of time series analysis in a financial context, both statistical methods and deep learning methods
• Experience in production software development environments, including version control, testing and test-driven development and change management
• Experience with multi-GPU model training
• Experience in the financial services sector, or in any highly regulated industry

Benefits

• Competitive compensation
• Flexible, hybrid work environment, 3 days in office, 2 days remote, per week.
• 2:1 401(k) match, up to 8% match immediately upon hire.
• Daily complimentary in-office lunch from local restaurants
• Endless free coffee and snacks to fuel your workday
• Monthly in office networking events and happy hours
• Associate Resource Groups (ARGs) and affinity groups for support and community building

Company Overview