Sr Engineer - Machine Learning - RegulatoryCedar Cares, Inc • Chicago, Illinois, United States

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Sr Engineer - Machine Learning - Regulatory

Cedar Cares, Inc

Chicago, Illinois, United States

Chicago, Illinois, United States

Über

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 provide the financial infrastructure that powers the global economy. As a leading provider of market infrastructure and tradable products, Cboe delivers cutting‑edge trading, clearing and investment solutions to market participants around the world. We’re building meaningful ways to support professional and personal development while strengthening the trust we’ve earned as a global market leader. Our teams are empowered to share ideas, actively pursue them and 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 to provide employees a safe space to network, share ideas and create opportunities. Location Overview: 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 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. 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 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 Qualifications 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 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 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 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 Salary Range 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. Visa / Eligibility 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. 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.
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Chicago, Illinois, United States

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English

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