DraftKings

Senior Machine Learning Engineer

DraftKings$134K — $168K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3+ years of experience with production Python applications and structured data (SQL and data modeling)
  • Strong fundamentals in software engineering - including object-oriented design, testing, and version control
  • Familiarity with ML Ops frameworks like model registries, orchestrations, and feature stores
  • Experience in building or maintaining data and feature pipelines in data-intensive environments
  • Understanding of the entire ML lifecycle from feature engineering to model serving
  • Proficient in debugging production issues across data, model, and infrastructure layers
  • A Bachelor's degree in Computer Science, Machine Learning, or a related field (Master's preferred)

Responsibilities

  • Design and maintain ETL and feature engineering pipelines for risk and payment applications
  • Develop and deploy production ML systems, monitoring their performance and reliability
  • Collaborate with data scientists to integrate models into the decision-making systems
  • Build reliable data workflows for feature transformations, model training, and deployment
  • Establish observability measures for data quality, model drift, and service reliability
  • Participate in code reviews and design discussions to uphold engineering best practices
  • Mentor junior engineers and contribute to documentation and process improvements

Benefits

  • Mentorship opportunities in a collaborative environment
  • Involvement in critical decision-making processes within the fintech space
  • Exposure to various aspects of machine learning and engineering practices
  • Support for continuous learning and professional development
  • Participation in on-call rotations to enhance system resilience
Full Job Description
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. The Fintech Data Science team builds and maintains systems that protect DraftKings and its customers from fraud, payment risk, and abuse. Our mission is to 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 that power risk and payment applications.
  • Develop production ML systems, from training and evaluation through deployment and monitoring.
  • Partner with data scientists to productionize models that integrate into DK's decisioning systems.
  • Build reliable, well-tested data workflows - from 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, helping to maintain strong engineering practices.
  • Mentor junior engineers and contribute to shared tooling, documentation, and process improvements across the DS organization.
  • Support on-call rotations and post-incident reviews to ensure continuous system improvement.


What you'll bring
  • 3+ years of experience writing production Python applications and working with structured data (SQL and data modeling).
  • Strong software engineering fundamentals - 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 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; able to translate technical solutions into operational outcomes.
  • Bachelor's degree in Computer Science, Machine Learning, or a related technical field (Master's preferred).


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 DraftKings

DraftKings is an American daily fantasy sports contest and sports betting operator. The company allows users to enter daily and weekly fantasy sports–related contests and win money based on individual player performances in five major American sports, Premier League and UEFA Champions League soccer, NASCAR auto racing, Canadian Football League, the XFL, mixed martial arts and Tennis. In August 2018, DraftKings launched DraftKings Sportsbook in New Jersey becoming the first legal mobile sports betting operator in the state. Since launching in New Jersey, DraftKings has opened mobile sports betting operations in Indiana, Pennsylvania, West Virginia and opened in New Hampshire December 30, 2019 after reaching contract with the New Hampshire Lottery. Retail sports betting is available in Iowa, Mississippi and New York. DraftKings Sportsbook mobile and retail sports betting products allow bettors in each state engage in betting for most major U.S. and international sports. As of April 2016, the majority of U.S. states consider fantasy sports a game of skill and not gambling. In November 2016, FanDuel and DraftKings, the two largest companies in the daily fantasy sports industry, reached an agreement to merge. However the merger was terminated in July 2017 due to it being blocked by the Federal Trade Commission as the combined company would have controlled a 90 percent of the market for daily fantasy sports. As of July 2017, DraftKings had eight million users.
Learn more about DraftKings
Size
3,400 employees
Market Cap
$4.9 billion
Industry
Net Income
-$577.9 million
Revenue
$292.3 million
NASDAQ

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