About the role
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're looking for a Senior Machine Learning Engineer to join our Engagement ML team, working as part of the cross-functional Onboarding squad in Discord's Growth organization. You'll design and build 0→1 end-to-end ML solutions that help brand-new users find their place on Discord: the servers, people, and content that turn a first session into a long-term connection to the product. If this excites you, keep reading!
What You'll Be Doing
- Design, build, and scale the recommendation systems that connect new users to communities and content, from candidate generation and ranking through to online serving.
- Solve cold-start personalization for users with little or no history on Discord, turning the limited signals available into recommendations for servers, communities, and content.
- Build and deploy ML models that lift new-user retention, combining purpose-built approaches with shared foundations such as user and server embeddings.
- Collaborate cross-functionally to shape the Onboarding roadmap, balancing fast learning experiments with the long-term complexity and scalability of the systems behind them
What you should have
- 5+ years of experience in Machine Learning, Data Science, or Applied Science, with a track record of shipping recommendation or personalization systems end to end.
- Hands-on experience building modern recommendation systems: retrieval and ranking pipelines, embedding-based retrieval (e.g. two-tower models), and deep learning models (e.g. transformers, multi-task learning).
- Strong proficiency in Python and ML frameworks such as PyTorch, JAX, or TensorFlow.
- Experience taking ML systems from ideation to production at scale, including feature pipelines, model serving, monitoring, and online experimentation.
- Strong product intuition and a passion for building 0→1 ML applications grounded in user feedback and real-world impact.
- Excellent communication and collaboration skills, able to serve as the ML voice on a cross-functional squad and keep stakeholders aligned on trade-offs, priorities, and progress.
- The ability to thrive in ambiguous environments, energized by tackling open-ended, technically challenging problems