Senior Software Engineer, Machine Learning (ads)

Discord Discord · Consumer · San Francisco, CA · Machine Learning

Senior Software Engineer, Machine Learning (Ads) at Discord. This role focuses on building and scaling ML capabilities for the Ads initiative, including ads measurement, targeting, and delivery ranking. The engineer will design, develop, and deploy ML models, optimize ad ranking, and scale ML infrastructure for low-latency decision-making. Experience in Ads ML, applied deep learning, and real-time ML inference is required.

What you'd actually do

  1. Design, develop, and deploy machine learning models for ads targeting and ranking.
  2. Develop sophisticated ML solutions such as identity graph to enhance ad targeting.
  3. Build and optimize ad ranking models to serve the most effective ads based on campaign objectives (e.g., app installs, link click).
  4. Improve ads targeting and ranking by leveraging both on-platform and off-platform signals.
  5. Scale our ML infrastructure to support an increasing number of concurrent ad campaigns while ensuring low-latency decision-making.

Skills

Required

  • 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
  • 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
  • Experience translating ML evaluation results and performance metrics into actionable product roadmap items
  • Ability to connect business objectives to ML solutions

Nice to have

  • Strong understanding of performance advertising and how ML impacts revenue and advertiser retention.
  • Knowledge of ad tech industry standards and ads ecosystem including targeting, retrieval, ranking, pacing, frequency, auction, etc.
  • Experience with large-scale recommendation systems.
  • Experience with large-scale data infrastructure and distributed computing

What the JD emphasized

  • 3+ years of experience specifically in Ads ML
  • Proven track record of designing, implementing, and scaling ML-driven ad systems in real-world applications.
  • Experience working with real-time ML inference

Other signals

  • building and scaling ML capabilities
  • early-stage Ads ML platform
  • foundational ML models
  • real-time ad-serving technologies
  • scale our ML infrastructure
  • low-latency decision-making