Senior Machine Learning Engineer

As a Senior Machine Learning Engineer at DraftKings, you will be instrumental in designing, implementing, and scaling production-grade data and machine learning pipelines. You will collaborate with data scientists, engineers, and product managers to build robust, observable, and scalable systems, specifically within the Fintech Data Science team to combat fraud and payment risk. Your work will ensure explainable and reliable decision-making across all financial and operational flows, from registration to withdrawals, contributing to the company's AI-driven future.

Must Have

• Design, build, and maintain ETL and feature engineering pipelines for risk and payments systems.
• Develop end-to-end production ML systems, from model training and evaluation to deployment and monitoring.
• Partner with data scientists to deploy models that integrate into real-time decisioning engines.
• Build robust, well-tested data workflows using SQL and Python.
• Implement observability tools to monitor data quality, model drift, and system performance.
• Contribute to code reviews, design sessions, and on-call support.
• Mentor junior engineers and improve shared tools, libraries, and documentation.
• Participate in incident response and postmortems.
• Bachelor's degree in Computer Science, Statistics, Machine Learning, or a related technical field.
• At least 3 years of experience writing production-grade Python code and working with SQL.
• Strong foundation in software engineering, including object-oriented design, testing, and version control.
• Experience with ML Ops tooling such as model registries, orchestration frameworks, or feature stores.
• Proven ability to build and maintain feature pipelines in data-heavy, real-time environments.
• Solid understanding of the ML lifecycle: feature engineering, training, validation, and serving.
• Ability to troubleshoot issues across data pipelines, model logic, and infrastructure.

Perks & Benefits

• Bonus
• Equity
• Benefits

AI is becoming an integral part of both our present and future, powering how work gets done today, guiding smarter decisions, and sparking bold ideas. It’s transforming how we enhance customer experiences, streamline operations, and unlock new possibilities. Our teams are energized by innovation and readily embrace emerging technology. We’re not waiting for the future to arrive. We’re shaping it, one bold step at a time. To those who see AI as a driver of progress, come build the future together.

The Crown Is Yours

As a Senior Machine Learning Engineer, you'll design, implement, and scale production-grade data and machine learning pipelines that drive measurable business outcomes. You'll partner closely with data scientists, engineers, and product managers to build systems that are well-structured, observable, and scalable. Sitting on the Fintech Data Science team, you'll build and maintain systems that protect us and our customers from fraud and payment risk. Your work will help enable explainable and reliable decision-making across all financial and operational flows, from registration and deposits, to gameplay and withdrawals.

What You'll Do

• Design, build, and maintain ETL and feature engineering pipelines for risk and payments systems.
• Develop end-to-end production ML systems, from model training and evaluation to deployment and monitoring.
• Partner with data scientists to deploy models that integrate into real-time decisioning engines.
• Build robust, well-tested data workflows using SQL and Python to support model development and scoring.
• Implement observability tools to monitor data quality, model drift, and system performance.
• Contribute to code reviews, design sessions, and on-call support to uphold strong engineering standards.
• Mentor junior engineers and improve shared tools, libraries, and documentation across the Data Science org.
• Participate in incident response and postmortems to continuously improve service reliability.

What You'll Bring

• Bachelor's degree in Computer Science, Statistics, Machine Learning, or a related technical field; Master's degree preferred.
• At least 3 years of experience writing production-grade Python code and working with SQL.
• Strong foundation in software engineering, including object-oriented design, testing, and version control.
• Experience with ML Ops tooling such as model registries, orchestration frameworks, or feature stores.
• Proven ability to build and maintain feature pipelines in data-heavy, real-time environments.
• Solid understanding of the ML lifecycle: feature engineering, training, validation, and serving.
• Ability to troubleshoot issues across data pipelines, model logic, and infrastructure.
• Excellent communication skills and a collaborative mindset.

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Join Our Team

We’re a publicly traded (NASDAQ: DKNG) technology company. 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. Don’t worry, we’ll guide you through the process if this is relevant to your role.

The US base salary range for this full-time position is 134,400.00 USD - 168,000.00 USD, plus bonus, equity, and benefits as applicable. Our ranges are determined by role, level, and location. The compensation information displayed on each job posting reflects the range for new hire pay rates for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific pay range and how that was determined during the hiring process. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

About Us

It’s simple, we believe life’s more fun with skin in the game. For that reason, we’re committed to responsibly creating the world’s favorite games and betting experiences. With offices around the globe, we believe we can continue to define what it means to be a technology company in sports entertainment. We love what we do, and think you will too.