Discord is about creating a space for everyone to find belonging in their lives. Hundreds of millions of people use Discord every week to have meaningful interactions.

The mission of the Content Recommendation team at Discord is to help users connect and engage with the online communities to create this belonging. We are working on enabling our users’ experiences with search, recommendations, and smart notifications. We are just starting to build these ML driven user experiences and if you are someone who is passionate about building things from scratch, this could be a great opportunity for you!

What You’ll Do:

• Care deeply about results and constraints and keep them in mind as they solve hard, unbounded problems; Work with product, data science, policy and UXR to create an ML driven product strategy.

• Collaborate with leadership and senior engineers across the team to define the technical vision and build on the technical roadmap for ML systems.

• Design and build large scale low latency machine learning systems for retrieval, ranking and personalization.

• Build generalizable infrastructure for retrieval, ranking and NLP, especially using MLOps stacks like TFX.

• Work with Engineering Managers and other Staff Engineers to make decisions for Discord and engineering function as a whole.

• Mentor the next generation of technical leaders at Discord.

What You’ll Need:

• Bachelor’s degree or higher in a quantitative field including Computer Science, Physics, Applied Math, Statistics or other quantitative fields.

• 7+ years of software development experience, or 5+ years with an advanced degree.

• Strong cross-functional capabilities.

• Strong product sense, maintain a high degree of empathy for your internal and external users and seek feedback from them about your work

• First Principles mindset and approach. Comfortable with the uncomfortable and able to be excited about working collaboratively to figure out solutions to complex problems, and then implementing them.

• You have helped define the architecture, tooling, and strategy for large-scale machine learning systems and tools.

• You have shipped large-scale recommendation/ search / adsML systems; and you’ve worked with distributed systems deployed at scale.

• You have a deep understanding of seminal approaches to retrieval and ranking; and you keep up with the industry trends and can assess new technologies that can help us evolve.

The US base salary range for this full-time position is ($230,000) to ($256,000) + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-relate4d skills, experience, and relevant education or training. Please note that the compensation details listed in US role posting reflect the base salary only, and do not include equity, or benefits.