Medal

Medal

Senior Frontend Engineer (React)

New York City · Senior

Sponsorship not specifiedDetected 8 days ago
JavaScriptJavaC++C#SwiftKotlinReactReduxiOSAndroidNode.jsFull-Stack DevelopmentGitRedisKubernetesTerraformCI/CDGitHub ActionsCircleCIRabbitMQA/B TestingValuationLeadership

About the role

  • Most of your work will be in React on our Electron app, where you'll iterate quickly to see which features stick, working directly with leadership and our community to ship features regularly.

Requirements

  • 5+ years of frontend engineering experience
  • Experience with React, Redux, Node, and Electron: You'll spend most of your time building things with React and will need to understand modern React practices and JavaScript in general

Nice to have

  • including Java, C#, and C++
  • A passion for games and the gaming communities, and a user of Discord and other gaming-adjacent products.
  • XP working on gaming-related projects is a plus
  • Electron, React, Redux, Styled Components & other modern web-based technologies
  • C# and C++ for native Windows recording & more
  • Swift for iOS, Kotlin for Android
  • Java, Redis, RabbitMQ, Kubernetes for backend
  • Terraform, Salt, GitHub Actions, CircleCI for IaC and CI/CD

Skills

  • Excellent understanding of code performance implications in production and confident with profiling tools

Company info

  • General Intuition is the frontier lab for acting in space and time.
  • We build large action models and world models that can perceive, predict, and act across virtual and physical environments.
  • General Intuition builds on the strength of Medal, the world's largest and fastest-growing platform for gaming clips, where millions of gamers capture, share, and discover new games every year.
  • We recently raised $320M at a $2.3B valuation led by Khosla Ventures with participation from General Catalyst, Eric Schmidt, and Jeff Bezos, to discover the next generation of real-world intelligence.

This listing is sourced directly from Medal's careers page and normalized into a canonical job model.