Senior Software Engineer, Machine Learning (Safety)

DiscordSan Francisco, CA
$220,000 - $247,500

About The Position

Discord has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there’s one thing that nearly everyone does: play video games. Discord plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games. We are seeking an experienced Senior Machine Learning Engineer to join our Safety ML team. This role focuses on building and deploying machine learning models that help keep Discord users safe, including real-time and batch systems for content understanding, risk evaluation, and account integrity. You will work closely with partners across product, engineering, design, policy, legal, and Trust and Safety to design and deliver effective ML solutions. This role reports to the Senior Manager of Machine Learning, Safety.

Requirements

  • 4+ years of experience in ML engineering or applied ML roles.
  • Strong coding skills in Python and fluency in ML frameworks such as PyTorch, JAX, or TensorFlow.
  • Experience building performant machine learning systems at scale and have driven the execution of projects from ideation to production.
  • Ability to think from first principles, approaching complex problems with creativity, clear reasoning, and pragmatic solutions.
  • A growth mindset: seeking feedback, reflecting on decisions, and continuously improving.
  • Excellent communication and collaboration skills, with a history of partnering effectively across engineering, data science, legal, policy, and product teams.
  • Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, or a related field (Physics, Math, Operations Research, etc.)

Responsibilities

  • Analyze data to identify risk patterns and inform the design of machine learning models
  • Build, iterate on, and evaluate models that detect risk and anomalous behavior
  • Work with product, engineering, legal, and Trust and Safety partners to deliver effective ML solutions
  • Work with partner teams in Trust & Safety to curate golden label sets at scale and improve data labeling techniques for model training
  • Deploy models into production systems, writing backend code as needed to ensure scalability and reliability, and monitor performance
  • Document modeling approaches and systems, and apply current machine learning best practices

Benefits

  • equity
  • benefits
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