Discord is used by over 200 million people every month for many different reasons, but there’s one thing that nearly everyone does on our platform: play video games
Over 90% of our users play games, spending a combined 1.5 billion hours playing thousands of unique titles on Discord each month. Discord plays a uniquely important role in the future of gaming. We are focused on making it easier and more fun for people to talk and hang out before, during, and after playing games
We are looking for a Senior Software Engineer specializing in Machine Learning to join our Revenue ML team at Discord. This team partners with our revenue product groups, focusing on both consumer revenue and our emerging Ads initiative. This role will specifically contribute to our Ads ML efforts, helping to build and scale ML capabilities in areas such as ads measurement, targeting, and delivery ranking
As part of this team, you will play a critical role in developing foundational ML models that enhance ad relevance, optimize performance, and drive revenue. This is a unique opportunity to work on an early-stage Ads ML platform and have a direct impact on the business's success. Our tech stack includes Python, ML frameworks like PyTorch and TensorFlow, large-scale data infrastructure, and real-time ad-serving technologies
What You'll Be Doing: Design, develop, and deploy machine learning models for ads targeting and ranking
Develop sophisticated ML solutions such as identity graph to enhance ad targeting
Build and optimize ad ranking models to serve the most effective ads based on campaign objectives (e.g., app installs, link click)
Improve ads targeting and ranking by leveraging both on-platform and off-platform signals
Collaborate cross-functionally with product, engineering, and business teams to define and execute on the Ads ML roadmap
Scale our ML infrastructure to support an increasing number of concurrent ad campaigns while ensuring low-latency decision-making
Drive research and implementation of state-of-the-art ML techniques in the field of online advertising
What You Should Have: 5+ years of experience as a Machine Learning Engineer or Data Scientist
3+ years of experience specifically in Ads ML (ads ranking, personalization, optimization, privacy-compliant user modeling, targeting, or measurement)
Strong proficiency in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow
Experience with applied deep learning (e.g transformers, embedding models)
Proven track record of designing, implementing, and scaling ML-driven ad systems in real-world applications
Experience working with real-time ML inference, A/B testing, and optimization frameworks