Senior Engineer - Machine Learning - Regulatory

Role Overview

Cboe Global Markets is the world's go-to derivatives and exchange network, providing trading solutions and products in multiple asset classes, including equities, derivatives, FX, and digital assets. Cboe’s Regulatory Division directly contributes to the company’s success by promoting fair, transparent, and trusted markets, through effective and efficient market oversight. We operate surveillance, examination, and investigative programs aimed at detecting and disciplining, or preventing, violative behavior.

Responsibilities

• Collaborate with the team on machine learning experiments across order book analysis, alert detection, and sequential financial data
• Develop and operate AI agent systems in production, applying ML engineering discipline to nondeterministic LLM-based software development workflows
• Own and evolve the team's ML training and deployment infrastructure on Snowflake
• Build production-quality data pipelines for processing terabytes of daily financial market data
• Raise the engineering bar through rigorous code review, architecture guidance, and mentorship of junior and mid-level engineers
• Design and develop production-quality, test-driven Python code
• Develop explainability and process-compliance solutions for AI and ML
• Effectively track and evaluate ML model performance across training, validation, inference, and monitoring
• Work in both on-premises and cloud environments
• Communicate technical information clearly and concisely to both technical and end-user audiences

Requirements

• Bachelor's degree in a quantitative field
• Production ML experience with time-series / sequential data — you've trained, deployed, and monitored models at scale, and you understand how time affects the structure of data: stationarity, regime change, leakage, and why a model that looks good in backtest fails live.
• Deep learning applied to temporal or representation problems — sequence models, embeddings/similarity over time-series, or equivalent.
• Data-reasoning instinct — able to say what the data is telling you and what data should go into a model in the first place, not just which model to reach for.
• Strong SQL and experience with large-scale datasets.
• Strong software-engineering foundation: 5+ years, primarily Python, with production practices (version control, automated testing, CI/CD, Docker) and comfort in an enterprise cloud data platform (Snowflake / Databricks / BigQuery, etc.) under real RBAC and governance constraints.
• Excellent written and verbal communication

Skills

• Machine Learning Skills

Benefits

• Fair and competitive salary and incentive compensation packages with an upside for overachievement
• Generous paid time off, including vacation, personal days, sick days and annual community service days
• Health, dental and vision benefits, including access to telemedicine and mental health services
• 2:1 401(k) match, up to 8% match immediately upon hire
• Discounted Employee Stock Purchase Plan Tax Savings Accounts for health, dependent and transportation
• Employee referral bonus program
• Volunteer opportunities to help you give back to your communities