Senior Engineer - Machine Learning - Regulatory

Job Description:

Building trusted markets - powered by our people

At Cboe Global Markets, we inspire our people to solve complex challenges together because what we do matters. We providethe financialinfrastructure that powers the global economy. As a leading provider of market infrastructure and tradable products, Cboe deliverscutting-edgetrading, clearing and investment solutions to market participants around the world.

We’rebuilding meaningful ways to support professional and personal development while strengthening the trustwe’veearned as a global market leader. Our teams are empowered to share ideas, actively pursuethemand bring on a challenge. As champions of internal mobility and access to opportunity, we encourage our people to “go for it” and equip our managers with the training to coach their teams to the next level. We strive toprovideemployeesa safe space to network, shareideasand create opportunities.

To supportstrong partnership and team connection, this role follows a four day in office work model.

Location Overview

Cboe HQislocated inthe historic Old Post Officedistrict,it’s a landmark that blends classic architecture with modern amenities. The building features expansive spaces withhigh ceilingsand large windows, offering an abundance of natural light and panoramic views of thecityskyline 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,afitness 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’sRegulatory Division directly contributes to the company’s success by promoting fair, transparent, and trusted markets, through effective and efficient market oversight. Weoperatesurveillance, examination, and investigative programs aimed at detecting and disciplining, or preventing, violative behavior.

Are you passionate aboutleveragingcutting-edgeArtificial 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’llhave the opportunity to work with a highly skilled team to prototype, train, and deploy ML models and AI applications thatmonitorfinancial markets generating terabytes of new data every trading day.You'llbe at the forefront of innovation,utilizingadvanced 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 onmachinelearning experiments across order book analysis, alert detection, and sequential financial data

• Develop andoperateAI 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

• 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.

• Solid 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

Machine Learning Skills

We work across deep learning, LLM agent systems, and classical ML.While youdon'tneedto knowall of these, you should have real depth in at least a coupleof 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 Perksof working for Cboe Global Markets

We value the total wellbeing of our people - including health, financial,personaland social wellness. We believe standard benefits like health insurance and fair pay area givenatany organization. Still, you shouldknowwe offer:

• Fair and competitive salary and incentive compensation packages with an upside for overachievement

• Generous paid time off, including vacation, personal days, sickdaysand 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% matchimmediatelyupon hire

• Discounted Employee Stock Purchase Plan

• Tax Savings Accounts for health,dependentand transportation

• Employee referral bonus program

• Volunteer opportunities to help you give back to your communities

Some of our associates’ favorite benefits andperksinclude:

• Complimentary lunch,snacksand coffee in any Cboe office

• Paid Tuitionassistanceand 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 CboeGlobal Markets

We’rereimagining the future of the workplace by focusing on what matters most, our people. Our journey is an inclusive one.We’reinvesting 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’rean 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 onour website andLinkedIn.

Equal Employment Opportunity

We'reproud 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, orveteran status. We are committed to fostering a workplace where all individuals are valued and respected.

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.

Salary Ranges (applicable for US locations only)

At Cboe, we are committed to providing a competitive, transparent, and market-informed total rewards program. The anticipated base salary range for this role is $154,275-$199,650, with actual compensation determined by job-related factors such as skills, relevant experience, education, internal alignment, and location.

This role may also be eligible for annual incentive compensation and, where applicable, participation in Cboe's long-term equity programs.

Additional information about Cboe's total rewards program, including benefits and other compensation components, can be found here: Total Rewards at 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.