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DraftKings

Senior Machine Learning Engineer, Platform

Posted 2 Days Ago
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Hybrid
London, Greater London, England
Senior level
Hybrid
London, Greater London, England
Senior level
The role involves designing and implementing ML platform components, collaborating with cross-functional teams, and mentoring junior engineers while ensuring production readiness of ML systems.
The summary above was generated by AI
At DraftKings, AI is becoming an integral part of both our present and future, powering how work gets done today, guiding smarter decisions, and sparking bold ideas. It's transforming how we enhance customer experiences, streamline operations, and unlock new possibilities. Our teams are energized by innovation and readily embrace emerging technology. We're not waiting for the future to arrive. We're shaping it, one bold step at a time. To those who see AI as a driver of progress, come build the future together.
The Crown Is Yours
As a Senior Machine Learning Platform Engineer at DraftKings, you will play a key role in designing, building, and improving the systems that enable scalable, reliable, and efficient data science projects across the company. You will take ownership of complex systems within our ML platform, partner with cross-functional data scientists and engineers, and contribute to the technical direction of our infrastructure. This is a great opportunity for someone who combines deep software engineering or data science skills with experience in machine learning operations (MLOps) and platform thinking.
What you'll do as a Senior ML Platform Engineer:
  • Lead the design and implementation of components across our ML platform, including model training pipelines, serving infrastructure, feature stores, and monitoring frameworks.
  • Drive engineering projects from technical planning through delivery and long-term maintenance.
  • Collaborate closely with data scientists, ML engineers, and infrastructure teams to align platform solutions with real-world use cases and evolving business needs.
  • Author and review technical designs for infrastructure that supports scalable, automated, and reproducible ML workflows.
  • Mentor junior engineers and contribute to raising the technical quality of the team through code reviews, design discussions, and knowledge sharing.
  • Contribute to the stability, performance, and observability of our ML systems by designing for production-readiness and supporting incident resolution.
  • Stay current with industry trends in MLOps and ML infrastructure and apply emerging best practices to improve platform efficiency and usability.

What you'll bring:
  • 4+ years of experience in ML Platform, MLOps, Data Engineering, or Infrastructure roles with a focus on platform development.
  • Proficiency in Python and experience with ML/DS libraries (e.g., scikit-learn, pandas, MLflow), along with strong software engineering fundamentals.
  • Experience with ML orchestration and CI/CD tooling (e.g., Airflow, MLflow, Argo, GitHub Actions or Jenkins).
  • Familiarity with cloud-native infrastructure (AWS, GCP, or Azure), containerization (Docker), orchestration (Kubernetes), and IaC tools (Terraform, Pulumi).
  • Experience working with data platforms such as Databricks or Spark, and a strong understanding of distributed data processing is a bonus.
  • A track record of owning complex technical projects and collaborating effectively across teams.
  • Strong communication skills and the ability to write clear documentation and articulate technical tradeoffs.
  • Bachelor's or advanced degree in Computer Science, Engineering, Data Science, or a related field.

#LI-EN1
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.

Top Skills

Airflow
Argo
AWS
Azure
Databricks
Docker
GCP
Github Actions
Jenkins
Kubernetes
Mlflow
Pandas
Pulumi
Python
Scikit-Learn
Spark
Terraform

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