Senior Machine Learning Engineer

DraftKings; United States; Remote; USD 134,000 - 168,000; Full time

Benefits offered by this job

Bonus potential

Equity

Benefits package

Job summary

DraftKings is hiring an engineer to build and operate cloud infrastructure and platform services for machine learning workloads. You will collaborate with data scientists, ML engineers, and infrastructure teams to create scalable, secure, and reliable systems.

Responsibilities include designing cloud infrastructure with IaC, creating CI/CD pipelines, owning production system reliability, and mentoring engineers. Nice to have experience with AWS, Kubernetes, Databricks, Spark or Kafka.

Qualifications

• Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience.
• 3+ years in software engineering focused on cloud infrastructure, platform or site reliability engineering, or data platforms.
• Strong Python skills for production applications and automation.
• Hands-on infrastructure-as-code experience with Terraform or Pulumi, including reusable modules and cloud resource management.
• Experience with distributed systems in the cloud; familiarity with networking, identity and access management, and security practices.
• Experience with CI/CD, workflow orchestration, and containers, plus familiarity with distributed data processing and batch or streaming workloads.
• Ownership of production systems and ability to lead technical work.

Responsibilities

• Design and maintain cloud infrastructure for ML workloads, covering compute, storage, networking, and access management through infrastructure as code.
• Create CI/CD pipelines, automation, and self-service tools for infrastructure provisioning and application delivery.
• Own production system design and operation, improving reliability, monitoring, and cost efficiency.
• Support high-volume batch and streaming data workloads, including real-time ingestion.
• Strengthen security and governance with access controls, infrastructure policies, and resource management.
• Develop reusable platform capabilities with partner teams, contribute to technical design and code reviews, and mentor engineers.

Skills

Python

Cloud infrastructure

CI/CD

Distributed systems

Security practices

Ownership

Monitoring

Education

Bachelor’s degree in CS/Engineering

Tools

Terraform

Pulumi

Kubernetes

Docker

Databricks

Spark

Kafka

Job description

Role overview

Build and operate cloud infrastructure and platform services that help teams train, deploy, and monitor machine learning models in production. You’ll work with data scientists, machine learning engineers, and infrastructure teams to make shared systems scalable, secure, reliable, and easier to use.

Responsibilities

• Design and maintain cloud infrastructure for machine learning workloads, covering compute, storage, networking, and access management through infrastructure as code.
• Create CI/CD pipelines, automation, and self-service tools for infrastructure provisioning and application delivery.
• Own production system design and operation, improving reliability, monitoring, and cost efficiency.
• Support high-volume batch and streaming data workloads, including real-time ingestion.
• Strengthen security and governance with access controls, infrastructure policies, and resource management.
• Develop reusable platform capabilities with partner teams, contribute to technical design and code reviews, and mentor engineers.

Requirements

• Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience.
• 3+ years in software engineering focused on cloud infrastructure, platform or site reliability engineering, or data platforms.
• Strong Python skills for production applications and automation.
• Hands-on infrastructure-as-code experience with Terraform or Pulumi, including reusable modules and cloud resource management.
• Experience with distributed systems in the cloud; familiarity with networking, identity and access management, and security practices.
• Experience with CI/CD, workflow orchestration, and containers, plus familiarity with distributed data processing and batch or streaming workloads.
• Ownership of production systems and ability to lead technical work.

Nice to have

• Experience with AWS, Kubernetes, Databricks, Spark, or Kafka.
• Prior machine learning experience is helpful but not required.

Benefits and work setup

• US base salary range: $134,400–$168,000, with bonus, equity, and benefits potentially available. Pay varies by location and job-related factors.
• A gaming license may be required, depending on the role and applicable jurisdiction.