220K–275K USD / year

Senior Machine Learning Engineer (Growth)

Machine learningWorkplace — San Francisco Bay Area
Published on 2026-11-04
These details were extracted automatically from the original listing. They may not be complete or fully up to date — it's worth checking the original job post.

About this role

Build and scale recommendation systems that help new Discord users discover communities, people, and content. The role focuses on cold-start personalization and improving new-user retention through end-to-end machine learning solutions.

About the company

Discord is a communication platform designed for creating communities, where users can connect via voice, video, and text. It serves gamers and various interest groups, offering tools for social interaction, collaboration, and community-building.

The team

Engagement ML team, working with the Onboarding squad in the Growth organization.

Stack

PythonPyTorchJAXTensorFlowTransformersTwo-tower modelsVector search

What you'll do

  • Build recommendation pipelines from candidate generation and ranking through online serving
  • Develop personalization for users with little or no Discord history
  • Deploy models to improve new-user retention
  • Collaborate on the Onboarding roadmap and balance experimentation with system scalability

What we're looking for

  • 5+ years in machine learning, data science, or applied science
  • Track record of shipping recommendation or personalization systems end to end
  • Experience with retrieval and ranking pipelines, embedding-based retrieval, and deep learning models
  • Proficiency in Python and an ML framework such as PyTorch, JAX, or TensorFlow
  • Experience taking ML systems to production, including feature pipelines, serving, monitoring, and online experimentation
  • Strong product intuition, communication, and cross-functional collaboration skills

Nice to have

  • Experience with cold-start personalization, onboarding, or preference elicitation
  • Experience with user representation models or social-graph recommendation signals
  • Consumer growth or engagement experience, such as activation or retention
  • Experience with large-scale recommendation systems, distributed computing, data infrastructure, or vector search

Benefits

  • Equity
  • Medical, dental, and vision insurance
  • 401(k) plan
  • Life and disability insurance
  • Paid time off
  • Paid parental leave
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