D

DraftKings

Online platform for fantasy sports betting

Senior Machine Learning Engineer - ML Platform Team

Platform EngineeringUpdated on Nov 13
Full-timeRemote in USARemote

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
  • At least 3 years of professional software engineering experience focused on cloud infrastructure, platform engineering, site reliability engineering, or data platforms.
  • Strong proficiency in Python, including experience developing, testing, and maintaining production-level applications and automation tools.
  • Hands-on experience with infrastructure as code tools such as Terraform or Pulumi, including developing reusable modules and managing cloud resources.
  • Experience designing and supporting distributed systems in cloud environments, preferably Amazon Web Services, with knowledge of networking, identity and access management, and security best practices.
  • Experience with CI/CD pipelines, workflow orchestration, and containerization technologies such as GitHub Actions, Jenkins, Argo, Airflow, or Docker.
  • Familiarity with distributed data processing technologies such as Databricks, Spark, or Kafka, and experience supporting batch or streaming data workloads.
  • A strong sense of ownership, experience supporting production systems, and the ability to lead complex technical initiatives while communicating effectively across teams.

Responsibilities

  • Design, build, and maintain scalable cloud infrastructure that supports machine learning workloads, including compute, storage, networking, and access management using Terraform.
  • Develop continuous integration and continuous deployment pipelines, automation, and self-service tools that streamline infrastructure provisioning and application deployments.
  • Own the design, deployment, and ongoing performance of production systems, driving improvements in reliability, monitoring, and cost efficiency.
  • Build and optimize data infrastructure to support high-volume batch and streaming workloads, including real-time data ingestion using Kafka and lakehouse technologies.
  • Strengthen platform security and governance through access controls, infrastructure policies, and resource management across shared cloud environments.
  • Collaborate with Data Scientists, Machine Learning Engineers, and Infrastructure Teams to develop reusable solutions that support model training, deployment, and monitoring.
  • Lead technical design discussions, review code, and mentor engineers while advancing engineering standards and best practices across the team.
  • Evaluate emerging cloud and infrastructure technologies to identify opportunities to improve platform scalability, performance, and operational efficiency.

Desired Qualifications

  • Kubernetes experience.
  • Prior machine learning experience.

About the Company

DraftKings

Online platform for fantasy sports betting

DraftKings runs an online gaming platform offering daily fantasy sports, sports betting, online casino games, and a marketplace for NFTs. The platform lets users enter cash-prize fantasy contests, place real-money bets on sports, and play casino games, while securely transferring digital assets. It differentiates itself with a broad, diversified product lineup and operates in tightly regulated markets to provide a secure environment. Its goal is to provide a comprehensive, compliant entertainment experience for sports fans, gamblers, and digital collectors while growing revenue across contests, bets, casino games, and NFT trading.

Company size
5,001-10,000
Company stage
IPO
Headquarters
Boston, MA
Founded
2012

Recently Posted Jobs

Explore more opportunities at DraftKings

See more jobs