Senior Machine Learning Engineer, Cboe
Regulatory
$154.3-199.7k
More information about location
4 days a week in office (Old Post Office district)
Market infrastructure and tradable product provider
Open for applications
Market infrastructure and tradable product provider
1001+ employees
Open for applications
$154.3-199.7k
More information about location
4 days a week in office (Old Post Office district)
1001+ employees
Company mission
To build a trusted, inclusive global marketplace that enables people to pursue a sustainable financial future.
Role
Who you are
- Passionate about leveraging cutting-edge Artificial Intelligence and Machine Learning to ensure the integrity and transparency of global financial markets
- 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
Desirable
- 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
What the job involves
- 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
- 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
- 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
Our take
Cboe provides market infrastructure and tradable products, including options, offering trading, clearing and investment solutions to market participants globally. Promising to operate an inclusive and trusted marketplace, its services ultimately enable participants to access a sustainable financial future.
The company is truly global, offering solutions across North America, Europe and Asia Pacific, and meeting the specific needs of its customers from where they are based. Its reach is echoed in the creation or acquisition of entirely new markets and market models, many of which served as the first of their kind, and hence have grown to become some of the largest, most relied upon out there.
Cboe intends to build upon the momentum that it continues to snowball year-on-year, growing its presence across North America whilst refining its latest innovations. For its participants, it will find new ways to enhance the overall equities markets while improving the customer experience on its platforms.
Steph
Company Specialist at Welcome to the Jungle
Insights
16% employee growth in 12 months
Company
Company HQ
West Loop Gate, Chicago, IL
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