Senior Machine Learning Engineer

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

In this Senior Machine Learning Engineer role at DraftKings in Boston, you will design, implement, and scale production-grade data and machine learning pipelines that support risk and payment applications. You will work across data science, engineering, and product to deliver observable and reliable systems for explainable decision-making.

What You Will Do

• Design, build, and maintain ETL and feature engineering pipelines for risk and payment applications.
• Develop production machine learning systems across training, evaluation, deployment, and monitoring.
• Partner with data scientists to productionize models and integrate them into DraftKings decisioning systems.
• Build reliable, well-tested data workflows spanning SQL-based feature transformations through model training and deployment.
• Establish observability and monitoring for data quality, model drift, and service reliability.
• Participate in code reviews, design discussions, and incident response to reinforce strong engineering practices.
• Mentor junior engineers and contribute to shared tooling, documentation, and process improvements across the data science organization.
• Support on-call rotations and post-incident reviews to drive ongoing system improvement.

Qualifications

• 3+ years of experience writing production Python applications and working with structured data (SQL and data modeling).
• Strong software engineering fundamentals including object-oriented 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 machine learning lifecycle, including feature engineering, training, and model serving.
• Ability to debug production issues across data, model, and infrastructure layers.
• Strong collaboration and communication skills, including translating technical solutions into operational outcomes.
• Bachelor’s degree in Computer Science, Machine Learning, or a related technical field (Master’s preferred).

Core Technologies

• Python
• SQL
• Data modeling
• Model registry
• Orchestrations
• Feature stores

Team and Mission

The Fintech Data Science team builds and maintains systems that help protect DraftKings and its customers from fraud, payment risk, and abuse. The team’s mission is to enable explainable and reliable decision-making across financial and operational flows, including registration and deposits, as well as gameplay and withdrawals.

Role Details

• Location: Boston, MA (onsite)
• Experience: 3+ years
• Compensation: USD 134,400 - 168,000 per year

Additional Information

• DraftKings is a publicly traded technology company headquartered in Boston (NASDAQ: DKNG).
• As a regulated gaming company, employment may require obtaining a gaming license issued by the appropriate state agency.