Senior Machine Learning Engineer (Growth)

Discord’s Engagement ML team is hiring a Senior Machine Learning Engineer (Growth) to help build end-to-end recommendation and cold-start personalization for onboarding new users.

Responsibilities

• Design, build, and scale recommendation systems that connect new users to servers, communities, and content, from candidate generation and ranking through online serving
• Develop cold-start personalization for users with little or no prior history on Discord, using limited available signals to power recommendations
• Build and deploy ML models that improve new-user retention, combining purpose-built methods with shared foundations such as user and server embeddings
• Partner cross-functionally to define and advance the Onboarding roadmap, balancing fast learning experiments with long-term system complexity and scalability

Requirements

• 5+ years of experience in Machine Learning, Data Science, or Applied Science, with a demonstrated track record shipping recommendation or personalization systems end to end
• Hands-on experience with modern recommendation systems, including:
  • Retrieval and ranking pipelines
  • Embedding-based retrieval (for example, two-tower models)
  • Deep learning models (for example, transformers, multi-task learning)
• Strong proficiency in Python and ML frameworks such as PyTorch, JAX, or TensorFlow
• Experience delivering ML systems from ideation to production at scale, including feature pipelines, model serving, monitoring, and online experimentation
• Strong product intuition and a drive to build 0 1 ML applications grounded in user feedback and real-world impact
• Excellent communication and collaboration skills, able to act as the ML voice on a cross-functional squad and align stakeholders on trade-offs, priorities, and progress
• Ability to thrive in ambiguous environments and tackle open-ended, technically challenging problems

Technologies

• Python
• PyTorch
• JAX
• TensorFlow
• transformers
• multi-task learning
• two-tower models

Bonus Points If You Have

• Experience with cold-start or new-user personalization, onboarding flows, or preference elicitation
• Experience building user representation models or applying social-graph signals to recommendation problems
• Experience working on growth or engagement problems for consumer products, including community and content recommendations, user activation, or retention
• Experience with large-scale recommendation systems, data infrastructure, distributed computing, and vector search

Benefits

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

Location: San Francisco Bay Area, CA (onsite)
Salary: USD 220,000 - 275,000 per year
Experience: 5+ years