Senior Software Engineer, Machine Learning

Summary

Join Discord's Revenue ML team as a Senior Software Engineer specializing in Machine Learning. You will contribute to our Ads ML efforts, building and scaling ML capabilities for ads measurement, targeting, and delivery ranking. This role involves developing foundational ML models to enhance ad relevance, optimize performance, and drive revenue. You will collaborate with product, engineering, and business teams and scale our ML infrastructure. This is an opportunity to work on an early-stage Ads ML platform and directly impact the business's success. The role is remote and offers a competitive salary and benefits package.

Requirements

• 5+ years of experience as a Machine Learning Engineer or Data Scientist
• 3+ years of experience specifically in Ads ML (ads ranking, personalization, optimization, user profiling, targeting, or measurement)
• Strong proficiency in Python and experience building ML models for large-scale applications
• 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
• Strong understanding of performance advertising and how ML impacts revenue and advertiser retention
• The ability to thrive in a fast-moving, ambiguous environment and build systems from the ground up

Responsibilities

• Design, develop, and deploy machine learning models for ads measurement, targeting, and ranking
• Improve our ads measurement framework by integrating first-party and third-party data to provide accurate campaign performance insights
• Develop sophisticated ML models to infer user interests, enhance ad targeting
• Build and optimize ad ranking models to serve the most effective ads based on campaign objectives (e.g., app installs, impression delivery)
• 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

Preferred Qualifications

• Experience with large-scale data infrastructure and distributed computing
• Familiarity with deep learning frameworks such as TensorFlow or PyTorch
• Knowledge of ad tech industry standards and third-party measurement solutions

Benefits

• Equity
• Benefits