Senior ML Engineer — Production Pipelines for Risk & Payments

DraftKings; Boston (MA); On-site; USD 134,000 - 168,000; Full time

Job summary

DraftKings in Boston is seeking a Senior Machine Learning Engineer to design, implement, and scale production-grade data and ML pipelines for risk and payment applications. You will work across data science, engineering, and product to deliver observable and reliable systems for explainable decision-making.

You will design ETL pipelines, develop production ML systems, and partner with data scientists to productionize models within DraftKings decisioning systems.

Qualifications

• 3+ years of production Python experience with structured data (SQL).
• Strong software engineering fundamentals: OO design, testing, and version control.
• Familiarity with ML Ops frameworks such as model registry, orchestrations, and feature stores.
• Experience building or maintaining data and feature pipelines in a data-heavy environment.
• Understanding of the ML lifecycle: feature engineering, training, and model serving.

Responsibilities

• Design, build, and maintain ETL and feature pipelines for risk and payment applications.
• Develop production ML systems across training, evaluation, deployment, and monitoring.
• Productionize models and integrate them into DraftKings decisioning systems.
• Build reliable data workflows spanning SQL transformations, model training and deployment.
• Establish observability and monitoring for data quality, drift, and reliability.
• Participate in code reviews, design discussions, and incident response to strengthen engineering practices.
• Mentor junior engineers and contribute to tooling, documentation, and processes.
• Support on-call rotations and post-incident reviews to drive system improvements.

Skills

Python

SQL

Data modeling

Testing

Version control

Education

Bachelor's degree in Computer Science / ML / related field

Tools

Model registry

Orchestrations

Feature stores

Job description

DraftKings in Boston is seeking a Senior Machine Learning Engineer to design, implement, and scale production-grade data and ML pipelines for risk and payment applications. You will work across data science, engineering, and product to deliver observable and reliable systems for explainable decision-making.

You will design ETL pipelines, develop production ML systems, and partner with data scientists to productionize models within DraftKings decisioning systems.