Senior Machine Learning Engineer (Growth)

Discord•San Francisco, CA

About The Position

Discord is seeking a Senior Machine Learning Engineer to join its Engagement ML team and work with the cross-functional Onboarding squad in the Growth organization. The role focuses on designing and building end-to-end machine learning solutions that help new users find communities, people, and content on Discord and develop lasting connections with the product. The engineer will build recommendation systems for new users, including candidate generation, ranking, and online serving. The work includes addressing cold-start personalization using limited user signals, developing and deploying models to improve new-user retention, and applying shared foundations such as user and server embeddings. The engineer will help shape the Onboarding roadmap with cross-functional partners, balancing rapid experimentation with the long-term scalability and complexity of the underlying systems. This is a full-time position with a base salary range of $220,000 to $275,000 USD, plus eligibility for equity and benefits. Applications are accepted on an ongoing basis.

Requirements

At least 5 years of experience in Machine Learning, Data Science, or Applied Science, with a record of shipping recommendation or personalization systems end to end.
Hands-on experience building modern recommendation systems, including retrieval and ranking pipelines, embedding-based retrieval such as two-tower models, and deep learning models such as transformers or multi-task learning.
Strong proficiency in Python and machine learning frameworks such as PyTorch, JAX, or TensorFlow.
Experience taking machine learning systems from ideation to production at scale, including feature pipelines, model serving, monitoring, and online experimentation.
Strong product intuition and enthusiasm for building 0-to-1 machine learning applications grounded in user feedback and real-world impact.
Excellent communication and collaboration skills, including the ability to represent machine learning on a cross-functional squad and align stakeholders on trade-offs, priorities, and progress.
Ability to thrive in ambiguous environments and take on open-ended, technically challenging problems.

Nice To Haves

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 with growth or engagement problems for consumer products, such as community and content recommendations, user activation, or retention.
Experience with large-scale recommendation systems, data infrastructure, distributed computing, and vector search.

Responsibilities

Design, build, and scale recommendation systems connecting new users to communities and content, from candidate generation and ranking through online serving.
Develop cold-start personalization for users with little or no Discord history, using limited signals to recommend servers, communities, and content.
Build and deploy machine learning models to improve new-user retention, using purpose-built approaches and shared foundations such as user and server embeddings.
Collaborate across functions to shape the Onboarding roadmap, balancing fast-learning experiments with long-term system complexity and scalability.