About The Position

Discord is seeking a Staff Machine Learning Engineer for its Consumer Revenue ML team. This team focuses on applying Machine Learning to Discord's core revenue streams, including Shop, Nitro, Server Subscriptions, and Gifting. They build ranking, targeting, and recommendation systems to connect users with relevant products, subscriptions, and content. The role is ideal for someone with experience leading organization-wide initiatives.

Requirements

  • 8+ years of experience in applied Machine Learning.
  • Ph.D. or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
  • Strong expertise in applied deep learning and mainstream RecSys model architecture (e.g., two-tower, transformer-based models, multi-task learning).
  • Strong proficiency in Python and ML frameworks such as PyTorch, JAX, or TensorFlow.
  • Track record of building ML systems from scratch in ambiguous, early-stage environments and scaling them to production.
  • Strong product and business intuition.
  • Excellent communication and collaboration skills.
  • Ability to thrive in ambiguous environments and tackle open-ended, technically challenging problems.

Nice To Haves

  • Experience building internal ML platform/tooling (shared data standards, targeting endpoints, recommender libraries) adopted by multiple product teams.
  • Familiarity with personalized marketing systems (lifecycle targeting, audience segmentation and lookalikes, campaign optimization).
  • Deep expertise in distributed training (e.g., PyTorch on GPU, Ray, Anyscale) and large-scale data processing pipelines (e.g., Chronon, Spark, Flink).

Responsibilities

  • Build and deploy machine learning systems for revenue-generating products.
  • Develop ranking, targeting, and recommendation systems.
  • Apply deep learning and mainstream RecSys model architectures.
  • Translate experiment results into roadmap decisions.
  • Lead cross-functional technical initiatives.
  • Educate and align stakeholders on technical progress and decisions.

Benefits

  • Equity
  • Benefits
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