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DiscordDiscordSan Francisco, CA

Senior Software Engineer, Machine Learning

Senior ML Engineer on Discord's Revenue ML team building and scaling ads targeting, ranking, and measurement models using PyTorch/TensorFlow to optimize ad performance and drive revenue. Requires 5+ years ML experience including 3+ years in Ads ML.

220k – 275k/yr
Hybrid7+ YOEML Engineering

About the role

Responsibilities

  • 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.

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, 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.
  • Experience translating ML evaluation results and performance metrics into actionable product roadmap items.
  • Ability to connect business objectives to ML solutions, with the flexibility to shift focus toward the highest-impact problems as priorities evolve.

Nice-to-Haves

  • 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.

Skills

PythonPyTorchTensorFlowDeep LearningTransformersembedding modelsreal-time ml inferenceA/B Testingads mlRecommendation Systemsdistributed computing

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