Cboe HQ is located in the historic Old Post Office district, it’s a landmark that blends classic architecture with modern amenities. The building features expansive spaces with high ceilings and large windows, offering an abundance of natural light and panoramic views of the city skyline and the Chicago River.

With its prime location in the heart of downtown, the OPO Building provides easy access to major transportation hubs, including Union Station and multiple CTA lines, making it convenient for commuters. The building is home to a variety of amenities, including restaurants, a fitness center, and collaborative workspaces, creating a vibrant and dynamic work environment in one of Chicago's most iconic areas.

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.

Are you passionate about leveraging cutting-edge Artificial Intelligence and Machine Learning to ensure the integrity and transparency of global financial markets? As a Senior Machine Learning Engineer - Regulatory at Cboe Global Markets, you’ll have the opportunity to work with a highly skilled team to prototype, train, and deploy ML models and AI applications that monitor financial markets generating terabytes of new data every trading day. You'll be at the forefront of innovation, utilizing advanced AI tools and scalable data engineering to transform complex data into actionable insights. If you thrive on tackling real-world challenges, excel in programming and large-scale data operations, and want to make a meaningful impact in a fast-paced, highly regulated environment, this is your chance to join a team where your expertise will help shape the future of market oversight. Step into a role where your ideas drive progress, and your contributions truly matter—apply now and help us turn data into value.

Your responsibilities will be:

• 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
• Work closely with complementary engineering teams
• Produce clear and thorough documentation, including ML proposals, experiment specifications, technical design, and testing scenarios
• Communicate technical information clearly and concisely to both technical and end-user audiences

The ideal candidate has:

• Bachelor's degree in a quantitative field
• 5+ years of professional software engineering experience, primarily in Python
• Strong SQL skills and experience working with large-scale datasets
• Production ML experience where you've trained, deployed, and monitored models at scale
• Experience with at least one enterprise cloud data platform (Snowflake, Databricks, BigQuery, or similar) including working within complex RBAC and governance constraints
• Experience with production software development practices: version control, automated testing, CI/CD
• Experience with containerized workflows (Docker)
• Demonstrated ability to mentor other engineers and influence engineering culture on a team
• Excellent written and verbal communication skills

Machine Learning Skills

We work across deep learning, LLM agent systems, and classical ML. While you don't need to know all of these, you should have real depth in at least a couple of these, and curiosity about the rest:

• Deep learning: PyTorch, custom training loops, architecture design and experimentation, multi-GPU distributed ML, experiment tracking, model lifecycle management
• LLMs: building with LLM APIs in production, prompt, context, and harness engineering as an engineering discipline, agent orchestration, full stack development using coding agents
• Time series and sequential modeling: TCNs, transformers, time-contrastive learning, or similar approaches on temporal data, as well as classical time series modeling (e.g. ARIMA)
• Classical ML: scikit-learn, weakly supervised clustering and anomaly detection, feature engineering, model evaluation for production decision systems

Benefits and Perks of working for Cboe Global Markets

We value the total wellbeing of our people – including health, financial, personal and social wellness. We believe standard benefits like health insurance and fair pay are a given at any organization. Still, you should know we offer:

• 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

Some of our associates’ favorite benefits and perks include:

• Complimentary lunch, snacks and coffee in any Cboe office
• Paid Tuition assistance and education opportunities
• Generous charitable giving company match
• Paid parental leave and fertility benefits
• On-site gyms and discounts to other fitness centers
• Paid Time Off

More About Cboe Global Markets

We’re reimagining the future of the workplace by focusing on what matters most, our people. Our journey is an inclusive one. We’re investing deeply in leadership programs and career development initiatives that ensure everyone has an equal chance to succeed.

We work with purpose, solving problems with ingenuity, collaboration, and a lot of passion. We’re an engaged and excited team connecting markets across borders and embracing growth in all its forms to achieve incredible outcomes.

Learn more about life at Cboe on our website and LinkedIn.

Equal Employment Opportunity

We're proud to be an equal opportunity employer do not discriminate against any employee or applicant for employment based on any legally protected characteristic, including race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, or veteran status. We are committed to fostering a workplace where all individuals are valued and respected.

LI-HL

LI-Hybrid

This position is not eligible for visa sponsorship. Candidates must be legally authorized to work in the United States without the need for employer sponsorship now or in the future.

Our pay ranges are determined by a number of factors, including, but not limited to, role, experience, level, and location. The national new hire base pay range for this job in the United States is $140,250-$173,250. This range represents the minimum and maximum base pay the company expects to offer for new hires working in the position full time. If you live in one of the following areas or if you work in a Cboe office in the following areas, the range may be higher according to the geographic differentials listed below:

US Geographic Differentials:

• 110%: Austin TX, Chicago IL, Denver CO, San Diego CA
• 115%: Los Angeles CA, Seattle WA
• 120%: Boston MA, Washington DC
• 125%: New York City NY
• 130%: San Francisco CA

Within the range, individual pay is determined by a number of factors, including, but not limited to, work location, job-related skills, experience, and relevant education or training. In addition to base pay, our total rewards program includes an annual variable pay program and benefits including healthcare (medical, dental and vision), 401 (k) with a generous company match, life and disability insurance, paid time off, market-leading tuition assistance, and much more! Your recruiter will provide more details about the total compensation package, including variable pay and benefits, during the hiring process. For further information on our total rewards program, visit TOTAL REWARDS @CBOE.

Any communication from Cboe regarding this position will only come from a Cboe recruiter who has a @cboe.com email or via LinkedIn Recruiter. Cboe does not use any other third party communication tools for recruiting purposes.