Machine Learning Engineer

5 Months ago • All levels • Data Analyst

Job Summary

Job Description

This Machine Learning Engineer role at DraftKings involves building and deploying ML models in a sportsbook platform. You'll work with Python, cloud environments, MLOps, and containerization to develop and productionize ML workloads. Experience with data science, Python, cloud environments, and MLOps is essential.
Must have:
  • Python experience
  • Cloud environment
  • Docker experience
  • MLOps platform
Good to have:
  • Kafka experience
  • Observability tooling
  • Object-oriented
  • Terraform knowledge
Perks:
  • Gaming license
  • Global team

Job Details

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

​Our Data Science team is composed of algorithm experts and data science technologists who leverage the power of data to deliver transformative experiences for our users and drive continued innovation. As a Machine Learning Engineer, you will be a creative thinker and utilize data, machine learning, and software development skills to craft high-impact solutions that transform our business.

What you'll do as a Machine Learning Engineer

  • Integrate statistical and machine learning models into production applications

  • Writing production quality code to deploy and run models in a sportsbook platform

  • Utilise our MLOps platform to productionise ML workloads

  • Create automatic tests to ensure model accuracy

  • Collaborate closely with product, developers, and delivery leads to move projects from ideation to development and deployment

  • Test that data flows work as expected and that models are well integrated in larger business context

What You'll bring

  • Experience using Python, and its application to data science and data engineering

  • Experience working in a cloud environment

  • Experience with docker and running containerised services (e.g Kubernetes, Docker Compose)

  • Experience of using observability tooling for production monitoring and alerting, such as DataDog, Grafana, Kibana

  • An understanding of event driven messaging systems (e.g Kafka, RabbitMQ), ideally with real-world experience

  • Experiencing with object-oriented programming

  • Knowledge of infrastructure as code (e.g terraform) is also beneficial

  • Understanding of data science and statistical modelling principles will be considered an asset

  • Bachelor’s degree in Statistics, Data Science, Mathematics, Computer Science, or a software engineering related field

#LI-SM1

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.

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