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.
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
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
Preferred
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
Cboe Global Markets (Cboe) is the leading exchange network for global derivatives, foreign exchange, digital asset and securities trading solutions.