Machine Learning Engineer, Platform

We’re defining what it means to build and deliver the most extraordinary sports and entertainment experiences. Our global team is trailblazing new markets, developing cutting-edge products, and shaping the future of responsible gaming.

Here, “impossible” isn’t part of our vocabulary. You’ll face some of the toughest but most rewarding challenges of your career. They’re worth it. Channeling your inner grit will accelerate your growth, help us win as a team, and create unforgettable moments for our customers.

The Crown Is Yours

As a Machine Learning Engineer on the Platform team, you will contribute to the development and maintenance of our machine learning ecosystem that empowers data scientists to build, deploy, and monitor models at scale. You'll work alongside experienced ML Platform Engineers and cross-functional teams to build robust, scalable, and automated infrastructure that supports the end-to-end ML lifecycle at DraftKings. This is a great opportunity for someone with a strong software engineering background and systems-level thinking. You'll have the chance to deepen your expertise in modern ML platform tooling while growing your skills in MLOps.

What you’ll do as an ML Platform Engineer:

• Collaborate with senior engineers and data scientists to design, build, and improve components of our MLOps stack, including model training pipelines, model serving infrastructure, feature stores, and model monitoring systems.

• Assist in the development of scalable and reproducible ML workflows using tools such as Airflow, MLflow, or similar orchestration and experiment tracking systems.

• Support the automation of model deployment and lifecycle management via CI/CD pipelines, containerization, and infrastructure-as-code.

• Help maintain a reliable ML platform through performance tuning, logging, alerting, and observability practices.

• Stay current with trends in ML infrastructure and tools, contributing ideas to improve our platform’s capabilities and efficiency.

What you’ll bring:

• 2+ years of experience in a Machine Learning Platform, MLOps, or Data Engineering role, or strong internship/project experience in the space.

• Familiarity with core MLOps concepts such as automated model training/deployment, monitoring, and experiment tracking.

• Proficiency in Python and common ML/DS libraries (e.g., scikit-learn, pandas, MLflow).

• Exposure to cloud platforms (e.g., AWS, GCP, or Azure) and tools like Docker, Kubernetes, or Terraform.

• Experience with data engineering and analytics platforms like Databricks.

• Understanding of distributed data processing with Spark is a plus.

• Familiarity with observability and monitoring tools such as Datadog is a plus.

• A strong desire to learn and grow within the ML infrastructure and MLOps domain.

• Bachelor’s or advanced degree in Computer Science, Data Science, Engineering, or a related field.

Join Our Team

We’re a publicly traded (NASDAQ: DKNG) technology company 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. 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 116,000.00 USD - 145,000.00 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.