Sr. Engineering Manager, Shopping Ads

Reddit Reddit · Consumer · United States · Remote · Ads Engineering

Engineering Manager for Reddit's Shopping Ads team, focusing on ML systems for targeting, retrieval, ranking, and engagement. The role requires strong technical leadership in ML systems, architecture, and production deployment, with a focus on scaling and operational excellence.

What you'd actually do

  1. Lead a high-performing team of software and machine learning engineers focused on Shopping Ads targeting, retrieval, ranking, and engagement models
  2. Drive technical execution for Dynamic Product Ads and Product Listing Ads across ads targeting, candidate retrieval, ranking integrations, model features, and engagement optimization
  3. Act as a hands-on technical leader by contributing to architecture reviews, technical design, debugging complex production issues, and guiding implementation decisions
  4. Partner closely with ML Platform, Ads Serving, Product, Data Science, Measurement, and Infrastructure teams to define roadmaps and deliver advertiser impact
  5. Improve scalability, latency, reliability, relevance, experimentation quality, and operational excellence across Shopping Ads systems

Skills

Required

  • software engineering
  • ML engineering
  • leading engineering teams
  • ads ranking
  • retrieval
  • targeting
  • recommendation systems
  • engagement modeling
  • ML-driven optimization systems
  • large-scale distributed systems
  • ML systems in production
  • technical lead manager (TLM)
  • systems thinking
  • debugging
  • prioritization
  • execution
  • communication
  • leadership

Nice to have

  • modern ads ecosystem trends
  • commerce advertising
  • recommendation architectures

What the JD emphasized

  • hands-on technical depth in ads ranking, retrieval, targeting, recommendation systems, engagement modeling, or ML-driven optimization systems
  • building and operating large-scale distributed systems or ML systems in production
  • technical lead manager (TLM)
  • systems thinking
  • debugging complex production issues
  • fast-moving production environments

Other signals

  • ML systems judgment
  • architecture
  • system design
  • technical problem solving
  • ML systems
  • ranking
  • retrieval
  • engagement modeling
  • targeting