Senior Machine Learning Engineer

Senior Machine Learning Engineer role focused on building production-grade data and ML systems for risk and payment decisions.

Responsibilities

• Design, build, and maintain ETL and feature engineering pipelines for risk and payment applications
• Develop production ML systems across training, evaluation, deployment, and monitoring
• Collaborate with data scientists to productionize models and integrate them into DK’s decisioning systems
• Create reliable, well-tested data workflows, including SQL-based feature transformations through model training and deployment
• Implement observability and monitoring for data quality, model drift, and service reliability
• Participate in code reviews, design discussions, and incident response to uphold engineering practices
• Mentor junior engineers and contribute to shared tooling, documentation, and process improvements across the DS organization
• Support on-call rotations and contribute to post-incident reviews for continuous improvement

Requirements

• 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 concepts such as model registry, orchestrations, and feature stores
• Experience building and maintaining data and feature pipelines in a data-heavy environment
• Understanding of the ML lifecycle, including feature engineering, training, and model serving
• Ability to debug production issues across data, model, and infrastructure layers
• Strong collaboration and communication skills; can translate technical solutions into operational outcomes
• Bachelor’s degree in Computer Science, Machine Learning, or a related technical field (Master’s preferred)

Technologies

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

Additional Information

• Design, implement, and scale production-grade data and machine learning pipelines for risk and payment applications
• Work with data scientists, engineers, and product managers to build systems that support explainable and reliable decision-making
• Fintech Data Science team builds and maintains systems that protect DraftKings and its customers from fraud, payment risk, and abuse
• Mission includes enabling explainable and reliable decision-making across financial and operational flows, from registration and deposits to gameplay and withdrawals

Location: Boston, MA (onsite)

Compensation: USD 134,400 - 168,000 per year

Minimum experience: 3 years

Company: DraftKings

• DraftKings is a publicly traded technology company (NASDAQ: DKNG) headquartered in Boston
• As a regulated gaming company, you may be required to obtain a gaming license issued by the appropriate state agency as a condition of employment
• Encouragement to apply even if you do not meet every box in the job description, or join the Talent Community